From 1857d6feb0ba5010f54e3a9c9a9209b944d1179c Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Sat, 14 Nov 2020 14:39:49 -0500 Subject: [PATCH 01/26] encrypt/decrypt [ghstack-poisoned] --- test/test_csprng.py | 43 ++++++++ torchcsprng/csrc/aes.h | 117 +++++++++++++++++++++ torchcsprng/csrc/block_cipher_2.h | 164 ++++++++++++++++++++++++++++++ torchcsprng/csrc/csprng.h | 73 +++++++++++++ 4 files changed, 397 insertions(+) create mode 100644 torchcsprng/csrc/block_cipher_2.h diff --git a/test/test_csprng.py b/test/test_csprng.py index b4c5443..43c7980 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -354,5 +354,48 @@ def test_const_generator(self): second = torch.empty(self.size, dtype=dtype, device=device).random_(generator=const_gen) self.assertTrue((first - second).max().abs() == 0) + def test_encrypt_decrypt(self): + key_size_bytes = 16 + block_size_bytes = 16 + + def sizeof(dtype): + if dtype == torch.bool: + return 1 + elif dtype.is_floating_point: + return torch.finfo(dtype).bits // 8 + else: + return torch.iinfo(dtype).bits // 8 + + for device in self.all_devices: + for key_dtype in self.all_dtypes: + key_size = key_size_bytes // sizeof(key_dtype) + key = torch.empty(key_size, dtype=key_dtype, device=device).random_() + for initial_dtype in self.all_dtypes: + for encrypted_dtype in self.all_dtypes: + for decrypted_dtype in self.all_dtypes: + for initial_size in [0, 4, 8, 15, 16, 23, 42]: + + encrypted_size = (initial_size * sizeof(initial_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(encrypted_dtype) + decrypted_size = (encrypted_size * sizeof(encrypted_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(decrypted_dtype) + + initial = torch.empty(initial_size, dtype=initial_dtype, device=device).random_() + encrypted = torch.empty(encrypted_size, dtype=encrypted_dtype, device=device).random_() + decrypted = torch.empty(decrypted_size, dtype=decrypted_dtype, device=device).random_() + + initial_np = initial.numpy().view(np.int8) + decrypted_np = decrypted.numpy().view(np.int8) + padding_size_bytes = initial_size * sizeof(initial_dtype) - decrypted_size * sizeof(decrypted_dtype) + if padding_size_bytes != 0: + decrypted_np = decrypted_np[:padding_size_bytes] + + csprng.encrypt(initial, encrypted, key, "aes128", "ecb") + + if initial_size > 8: + self.assertFalse(np.array_equal(initial_np, decrypted_np)) + + csprng.decrypt(encrypted, decrypted, key, "aes128", "ecb") + + self.assertTrue(np.array_equal(initial_np, decrypted_np)) + if __name__ == '__main__': unittest.main() diff --git a/torchcsprng/csrc/aes.h b/torchcsprng/csrc/aes.h index 09596f1..bd41928 100644 --- a/torchcsprng/csrc/aes.h +++ b/torchcsprng/csrc/aes.h @@ -97,6 +97,24 @@ TORCH_CSPRNG_CONSTANT const uint8_t sbox[256] = { 0xe1, 0xf8, 0x98, 0x11, 0x69, 0xd9, 0x8e, 0x94, 0x9b, 0x1e, 0x87, 0xe9, 0xce, 0x55, 0x28, 0xdf, 0x8c, 0xa1, 0x89, 0x0d, 0xbf, 0xe6, 0x42, 0x68, 0x41, 0x99, 0x2d, 0x0f, 0xb0, 0x54, 0xbb, 0x16 }; +TORCH_CSPRNG_CONSTANT const uint8_t rsbox[256] = { + 0x52, 0x09, 0x6a, 0xd5, 0x30, 0x36, 0xa5, 0x38, 0xbf, 0x40, 0xa3, 0x9e, 0x81, 0xf3, 0xd7, 0xfb, + 0x7c, 0xe3, 0x39, 0x82, 0x9b, 0x2f, 0xff, 0x87, 0x34, 0x8e, 0x43, 0x44, 0xc4, 0xde, 0xe9, 0xcb, + 0x54, 0x7b, 0x94, 0x32, 0xa6, 0xc2, 0x23, 0x3d, 0xee, 0x4c, 0x95, 0x0b, 0x42, 0xfa, 0xc3, 0x4e, + 0x08, 0x2e, 0xa1, 0x66, 0x28, 0xd9, 0x24, 0xb2, 0x76, 0x5b, 0xa2, 0x49, 0x6d, 0x8b, 0xd1, 0x25, + 0x72, 0xf8, 0xf6, 0x64, 0x86, 0x68, 0x98, 0x16, 0xd4, 0xa4, 0x5c, 0xcc, 0x5d, 0x65, 0xb6, 0x92, + 0x6c, 0x70, 0x48, 0x50, 0xfd, 0xed, 0xb9, 0xda, 0x5e, 0x15, 0x46, 0x57, 0xa7, 0x8d, 0x9d, 0x84, + 0x90, 0xd8, 0xab, 0x00, 0x8c, 0xbc, 0xd3, 0x0a, 0xf7, 0xe4, 0x58, 0x05, 0xb8, 0xb3, 0x45, 0x06, + 0xd0, 0x2c, 0x1e, 0x8f, 0xca, 0x3f, 0x0f, 0x02, 0xc1, 0xaf, 0xbd, 0x03, 0x01, 0x13, 0x8a, 0x6b, + 0x3a, 0x91, 0x11, 0x41, 0x4f, 0x67, 0xdc, 0xea, 0x97, 0xf2, 0xcf, 0xce, 0xf0, 0xb4, 0xe6, 0x73, + 0x96, 0xac, 0x74, 0x22, 0xe7, 0xad, 0x35, 0x85, 0xe2, 0xf9, 0x37, 0xe8, 0x1c, 0x75, 0xdf, 0x6e, + 0x47, 0xf1, 0x1a, 0x71, 0x1d, 0x29, 0xc5, 0x89, 0x6f, 0xb7, 0x62, 0x0e, 0xaa, 0x18, 0xbe, 0x1b, + 0xfc, 0x56, 0x3e, 0x4b, 0xc6, 0xd2, 0x79, 0x20, 0x9a, 0xdb, 0xc0, 0xfe, 0x78, 0xcd, 0x5a, 0xf4, + 0x1f, 0xdd, 0xa8, 0x33, 0x88, 0x07, 0xc7, 0x31, 0xb1, 0x12, 0x10, 0x59, 0x27, 0x80, 0xec, 0x5f, + 0x60, 0x51, 0x7f, 0xa9, 0x19, 0xb5, 0x4a, 0x0d, 0x2d, 0xe5, 0x7a, 0x9f, 0x93, 0xc9, 0x9c, 0xef, + 0xa0, 0xe0, 0x3b, 0x4d, 0xae, 0x2a, 0xf5, 0xb0, 0xc8, 0xeb, 0xbb, 0x3c, 0x83, 0x53, 0x99, 0x61, + 0x17, 0x2b, 0x04, 0x7e, 0xba, 0x77, 0xd6, 0x26, 0xe1, 0x69, 0x14, 0x63, 0x55, 0x21, 0x0c, 0x7d }; + // The round constant word array, Rcon[i], contains the values given by // x to the power (i-1) being powers of x (x is denoted as {02}) in the field GF(2^8) TORCH_CSPRNG_CONSTANT const uint8_t Rcon[11] = { @@ -104,6 +122,8 @@ TORCH_CSPRNG_CONSTANT const uint8_t Rcon[11] = { #define getSBoxValue(num) (sbox[(num)]) +#define getSBoxInvert(num) (rsbox[(num)]) + // This function produces Nb(Nr+1) round keys. The round keys are used in each round to decrypt the states. TORCH_CSPRNG_HOST_DEVICE void KeyExpansion(uint8_t* RoundKey, const uint8_t* Key){ unsigned int i, j, k; @@ -257,6 +277,78 @@ TORCH_CSPRNG_HOST_DEVICE void MixColumns(state_t* state) } } +TORCH_CSPRNG_HOST_DEVICE uint8_t Multiply(uint8_t x, uint8_t y) +{ + return (((y & 1) * x) ^ + ((y>>1 & 1) * xtime(x)) ^ + ((y>>2 & 1) * xtime(xtime(x))) ^ + ((y>>3 & 1) * xtime(xtime(xtime(x)))) ^ + ((y>>4 & 1) * xtime(xtime(xtime(xtime(x)))))); /* this last call to xtime() can be omitted */ +} + +// MixColumns function mixes the columns of the state matrix. +// The method used to multiply may be difficult to understand for the inexperienced. +// Please use the references to gain more information. +TORCH_CSPRNG_HOST_DEVICE void InvMixColumns(state_t* state) +{ + int i; + uint8_t a, b, c, d; + for (i = 0; i < 4; ++i) + { + a = (*state)[i][0]; + b = (*state)[i][1]; + c = (*state)[i][2]; + d = (*state)[i][3]; + + (*state)[i][0] = Multiply(a, 0x0e) ^ Multiply(b, 0x0b) ^ Multiply(c, 0x0d) ^ Multiply(d, 0x09); + (*state)[i][1] = Multiply(a, 0x09) ^ Multiply(b, 0x0e) ^ Multiply(c, 0x0b) ^ Multiply(d, 0x0d); + (*state)[i][2] = Multiply(a, 0x0d) ^ Multiply(b, 0x09) ^ Multiply(c, 0x0e) ^ Multiply(d, 0x0b); + (*state)[i][3] = Multiply(a, 0x0b) ^ Multiply(b, 0x0d) ^ Multiply(c, 0x09) ^ Multiply(d, 0x0e); + } +} + +// The SubBytes Function Substitutes the values in the +// state matrix with values in an S-box. +TORCH_CSPRNG_HOST_DEVICE void InvSubBytes(state_t* state) +{ + uint8_t i, j; + for (i = 0; i < 4; ++i) + { + for (j = 0; j < 4; ++j) + { + (*state)[j][i] = getSBoxInvert((*state)[j][i]); + } + } +} + +TORCH_CSPRNG_HOST_DEVICE void InvShiftRows(state_t* state) +{ + uint8_t temp; + + // Rotate first row 1 columns to right + temp = (*state)[3][1]; + (*state)[3][1] = (*state)[2][1]; + (*state)[2][1] = (*state)[1][1]; + (*state)[1][1] = (*state)[0][1]; + (*state)[0][1] = temp; + + // Rotate second row 2 columns to right + temp = (*state)[0][2]; + (*state)[0][2] = (*state)[2][2]; + (*state)[2][2] = temp; + + temp = (*state)[1][2]; + (*state)[1][2] = (*state)[3][2]; + (*state)[3][2] = temp; + + // Rotate third row 3 columns to right + temp = (*state)[0][3]; + (*state)[0][3] = (*state)[1][3]; + (*state)[1][3] = (*state)[2][3]; + (*state)[2][3] = (*state)[3][3]; + (*state)[3][3] = temp; +} + TORCH_CSPRNG_HOST_DEVICE void encrypt(uint8_t* state, const uint8_t* key) { uint8_t RoundKey[176]; KeyExpansion(RoundKey, key); @@ -284,4 +376,29 @@ TORCH_CSPRNG_HOST_DEVICE void encrypt(uint8_t* state, const uint8_t* key) { AddRoundKey(Nr, (state_t*)state, RoundKey); } +TORCH_CSPRNG_HOST_DEVICE void decrypt(uint8_t* state, const uint8_t* key) { + uint8_t RoundKey[176]; + KeyExpansion(RoundKey, key); + + uint8_t round = 0; + + // Add the First round key to the state before starting the rounds. + AddRoundKey(Nr, (state_t*)state, RoundKey); + + // There will be Nr rounds. + // The first Nr-1 rounds are identical. + // These Nr rounds are executed in the loop below. + // Last one without InvMixColumn() + for (round = (Nr - 1); ; --round) + { + InvShiftRows((state_t*)state); + InvSubBytes((state_t*)state); + AddRoundKey(round, (state_t*)state, RoundKey); + if (round == 0) { + break; + } + InvMixColumns((state_t*)state); + } +} + }}} diff --git a/torchcsprng/csrc/block_cipher_2.h b/torchcsprng/csrc/block_cipher_2.h new file mode 100644 index 0000000..d7a6925 --- /dev/null +++ b/torchcsprng/csrc/block_cipher_2.h @@ -0,0 +1,164 @@ +/* + * Copyright (c) Facebook, Inc. and its affiliates. + * All rights reserved. + * + * This source code is licensed under the BSD-style license found in the + * LICENSE file in the root directory of this source tree. + */ + +#pragma once + +#include "macros.h" +#include +#include +#include "OffsetCalculator.cuh" +#include +#include +#include + +#if defined(__CUDACC__) || defined(__HIPCC__) +#include +#include +#endif + +#if defined(__CUDACC__) || defined(__HIPCC__) +#define UNROLL_IF_CUDA #pragma unroll +#else +#define UNROLL_IF_CUDA +#endif + +namespace torch { +namespace csprng { + +template +TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper_2(int64_t idx, cipher_t cipher, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { + + uint8_t block[block_size]; + memset(&block, 0, block_size); // is it ok to use zeros as padding? + + for (auto i = 0; i < block_size / input_type_size; ++i) { + const auto linear_index = idx * block_size / input_type_size + i; + for (auto j = 0; j < input_type_size; ++j) { + const auto byte_index = i * input_type_size + j; + if (linear_index < input_numel) { + block[byte_index] = reinterpret_cast(input_ptr)[input_index_calc(linear_index) + j]; + } + } + } + + cipher(idx, block); + + for (auto i = 0; i < block_size / output_type_size; ++i) { + const auto linear_index = idx * block_size / output_type_size + i; + for (auto j = 0; j < output_type_size; ++j) { + const auto byte_index = i * output_type_size + j; + if (linear_index < output_numel) { + reinterpret_cast(output_ptr)[output_index_calc(linear_index) + j] = block[byte_index]; + } + } + } +} + +#if defined(__CUDACC__) || defined(__HIPCC__) +template +__global__ static void block_cipher_kernel_cuda_2(cipher_t cipher, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { + const auto idx = blockIdx.x * blockDim.x + threadIdx.x; + block_cipher_kernel_helper_2(idx, cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc); +} +#endif + +template +static void block_cipher_kernel_cpu_serial_2(int64_t begin, int64_t end, cipher_t cipher, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { + for (auto idx = begin; idx < end; ++idx) { + block_cipher_kernel_helper_2(idx, cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc); + } +} + +template +static void block_cipher_kernel_cpu_2(int64_t total, cipher_t cipher, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { + if (total < at::internal::GRAIN_SIZE || at::get_num_threads() == 1) { + block_cipher_kernel_cpu_serial_2(0, total, cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc); + } else { + at::parallel_for(0, total, at::internal::GRAIN_SIZE, [&](int64_t begin, int64_t end) { + block_cipher_kernel_cpu_serial_2(begin, end, cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc); + }); + } +} + +template +void block_cipher_2(Tensor input, Tensor output, cipher_t cipher, int block_size) { + if (input.numel() == 0) { + return; + } + + const auto input_ptr = input.data_ptr(); + const auto input_numel = input.numel(); + const auto input_type_size = input.element_size(); + const auto input_iter = TensorIterator::nullary_op(input); + const auto input_offset_calc = make_offset_calculator<1>(input_iter); + const std::function input_index_calc_contiguous = [input_type_size] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? + return li * input_type_size; + }; + const std::function input_index_calc_non_contiguous = [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? + return input_offset_calc.get(li)[0]; + }; + const auto input_index_calc = input.is_contiguous() ? input_index_calc_contiguous : input_index_calc_non_contiguous; + + const auto output_ptr = output.data_ptr(); + const auto output_numel = output.numel(); + const auto output_type_size = output.element_size(); + const auto output_iter = TensorIterator::nullary_op(output); + const auto output_offset_calc = make_offset_calculator<1>(output_iter); + const std::function output_index_calc_contiguous = [output_type_size] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? + return li * output_type_size; + }; + const std::function output_index_calc_non_contiguous = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? + return output_offset_calc.get(li)[0]; + }; + const auto output_index_calc = output.is_contiguous() ? output_index_calc_contiguous : output_index_calc_non_contiguous; + + TORCH_CHECK((input_numel * input_type_size + block_size - 1) / block_size * block_size == output_numel * output_type_size, "wrong size"); + + const auto size_in_bytes = input_numel * input_type_size; + + const auto block = 256; + const auto grid = (size_in_bytes + (block * block_size) - 1) / (block * block_size); + + if (input.device().type() == at::kCPU) { + block_cipher_kernel_cpu_2(grid * block, cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc + ); + } else if (input.device().type() == at::kCUDA) { +#if defined(__CUDACC__) || defined(__HIPCC__) + auto stream = at::cuda::getCurrentCUDAStream(); + block_cipher_kernel_cuda_2<<>>(cipher, block_size, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc + ); + AT_CUDA_CHECK(cudaGetLastError()); +#else + TORCH_CHECK(false, "torchcsprng was compiled without CUDA support"); +#endif + } else { + TORCH_CHECK(false, "block_cipher supports only CPU and CUDA devices"); + } +} + +}} diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index f1fa0f9..def4d31 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -18,6 +18,7 @@ #include #include "macros.h" #include "block_cipher.h" +#include "block_cipher_2.h" #include "aes.h" #if defined(__CUDACC__) || defined(__HIPCC__) @@ -416,6 +417,76 @@ Tensor& randperm_generator_out(Tensor& result, int64_t n, c10::optional(key.contiguous().data_ptr()); + if (mode == "ecb") { + block_cipher_2(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + aes::encrypt(block, key_bytes); + }, + aes::block_t_size + ); + } else if (mode == "ctr") { + block_cipher_2(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + uint8_t idx_block[aes::block_t_size]; + *(reinterpret_cast(idx_block)) = idx; + aes::encrypt(idx_block, key_bytes); + for (size_t i = 0; i < aes::block_t_size; i++) { + block[i] ^= idx_block[i]; + } + }, + aes::block_t_size + ); + } else { + TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); + } + return output; +} + +// Let's assume that input and output have integral dtype, so there is no transform for now. +Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { +// TORCH_CHECK(input.numel() * input.itemsize() == output.numel() * output.itemsize(), "input and output tensors must have the same size in byte"); + if (cipher == "aes128") { + TORCH_CHECK(key.element_size() * key.numel() == 16, "key tensor must have 16 bytes(128 bits)"); + } else { + TORCH_CHECK(false, "encrypt/decrypt supports \"aes128\" cipher, \"", cipher, "\" is not supported."); + } + const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); + if (mode == "ecb") { + block_cipher_2(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + aes::decrypt(block, key_bytes); + }, + aes::block_t_size + ); + } else if (mode == "ctr") { + block_cipher_2(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + uint8_t idx_block[aes::block_t_size]; + *(reinterpret_cast(idx_block)) = idx; + aes::decrypt(idx_block, key_bytes); + for (size_t i = 0; i < aes::block_t_size; i++) { + block[i] ^= idx_block[i]; + } + }, + aes::block_t_size + ); + } else { + TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); + } + return output; +} + +// ==================================================================================================================== + Generator create_random_device_generator(c10::optional token = c10::nullopt) { if (token.has_value()) { return make_generator(*token); @@ -481,4 +552,6 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { m.def("create_mt19937_generator", &create_mt19937_generator, py::arg("seed") = nullptr); m.def("aes128_key_tensor", &aes128_key_tensor_pybind); m.def("create_const_generator", &create_const_generator); + m.def("encrypt", &encrypt_pybind); + m.def("decrypt", &decrypt_pybind); } From 1737f817124c4bfbe5250ef9720e66decd53d2b9 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Mon, 16 Nov 2020 15:16:38 -0500 Subject: [PATCH 02/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- test/test_csprng.py | 32 ++++++++--------- torchcsprng/csrc/block_cipher_2.h | 60 ++++++++++++++++++------------- torchcsprng/csrc/csprng.h | 4 ++- 3 files changed, 54 insertions(+), 42 deletions(-) diff --git a/test/test_csprng.py b/test/test_csprng.py index 43c7980..513d42d 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -374,28 +374,28 @@ def sizeof(dtype): for encrypted_dtype in self.all_dtypes: for decrypted_dtype in self.all_dtypes: for initial_size in [0, 4, 8, 15, 16, 23, 42]: + for mode in ["ecb", "ctr"]: + encrypted_size = (initial_size * sizeof(initial_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(encrypted_dtype) + decrypted_size = (encrypted_size * sizeof(encrypted_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(decrypted_dtype) - encrypted_size = (initial_size * sizeof(initial_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(encrypted_dtype) - decrypted_size = (encrypted_size * sizeof(encrypted_dtype) + block_size_bytes - 1) // block_size_bytes * block_size_bytes // sizeof(decrypted_dtype) + initial = torch.empty(initial_size, dtype=initial_dtype, device=device).random_() + encrypted = torch.empty(encrypted_size, dtype=encrypted_dtype, device=device).random_() + decrypted = torch.empty(decrypted_size, dtype=decrypted_dtype, device=device).random_() - initial = torch.empty(initial_size, dtype=initial_dtype, device=device).random_() - encrypted = torch.empty(encrypted_size, dtype=encrypted_dtype, device=device).random_() - decrypted = torch.empty(decrypted_size, dtype=decrypted_dtype, device=device).random_() + initial_np = initial.numpy().view(np.int8) + decrypted_np = decrypted.numpy().view(np.int8) + padding_size_bytes = initial_size * sizeof(initial_dtype) - decrypted_size * sizeof(decrypted_dtype) + if padding_size_bytes != 0: + decrypted_np = decrypted_np[:padding_size_bytes] - initial_np = initial.numpy().view(np.int8) - decrypted_np = decrypted.numpy().view(np.int8) - padding_size_bytes = initial_size * sizeof(initial_dtype) - decrypted_size * sizeof(decrypted_dtype) - if padding_size_bytes != 0: - decrypted_np = decrypted_np[:padding_size_bytes] + csprng.encrypt(initial, encrypted, key, "aes128", mode) - csprng.encrypt(initial, encrypted, key, "aes128", "ecb") + if initial_size > 8: + self.assertFalse(np.array_equal(initial_np, decrypted_np)) - if initial_size > 8: - self.assertFalse(np.array_equal(initial_np, decrypted_np)) + csprng.decrypt(encrypted, decrypted, key, "aes128", mode) - csprng.decrypt(encrypted, decrypted, key, "aes128", "ecb") - - self.assertTrue(np.array_equal(initial_np, decrypted_np)) + self.assertTrue(np.array_equal(initial_np, decrypted_np)) if __name__ == '__main__': unittest.main() diff --git a/torchcsprng/csrc/block_cipher_2.h b/torchcsprng/csrc/block_cipher_2.h index d7a6925..0eca492 100644 --- a/torchcsprng/csrc/block_cipher_2.h +++ b/torchcsprng/csrc/block_cipher_2.h @@ -30,37 +30,47 @@ namespace torch { namespace csprng { -template -TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper_2(int64_t idx, cipher_t cipher, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - - uint8_t block[block_size]; - memset(&block, 0, block_size); // is it ok to use zeros as padding? - +template +TORCH_CSPRNG_HOST_DEVICE static void copy_input_to_block(int64_t idx, uint8_t* block, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc) { for (auto i = 0; i < block_size / input_type_size; ++i) { - const auto linear_index = idx * block_size / input_type_size + i; - for (auto j = 0; j < input_type_size; ++j) { - const auto byte_index = i * input_type_size + j; - if (linear_index < input_numel) { - block[byte_index] = reinterpret_cast(input_ptr)[input_index_calc(linear_index) + j]; - } + const auto linear_index = idx * (block_size / input_type_size) + i; + if (linear_index < input_numel) { + std::memcpy( + &(block[i * input_type_size]), + &(reinterpret_cast(input_ptr)[input_index_calc(linear_index)]), + input_type_size + ); } } +} - cipher(idx, block); - +template +TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* block, int block_size, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { for (auto i = 0; i < block_size / output_type_size; ++i) { const auto linear_index = idx * block_size / output_type_size + i; - for (auto j = 0; j < output_type_size; ++j) { - const auto byte_index = i * output_type_size + j; - if (linear_index < output_numel) { - reinterpret_cast(output_ptr)[output_index_calc(linear_index) + j] = block[byte_index]; - } + if (linear_index < output_numel) { + std::memcpy( + &(reinterpret_cast(output_ptr)[output_index_calc(linear_index)]), + &(block[i * output_type_size]), + output_type_size + ); } } } +template +TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper_2(int64_t idx, cipher_t cipher, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { + uint8_t block[block_size]; + memset(&block, 0, block_size); // is it ok to use zeros as padding? + copy_input_to_block(idx, block, block_size, input_ptr, input_numel, input_type_size, input_index_calc); + cipher(idx, block); + copy_block_to_output(idx, block, block_size, output_ptr, output_numel, output_type_size, output_index_calc); +} + #if defined(__CUDACC__) || defined(__HIPCC__) template __global__ static void block_cipher_kernel_cuda_2(cipher_t cipher, int block_size, @@ -137,16 +147,16 @@ void block_cipher_2(Tensor input, Tensor output, cipher_t cipher, int block_size const auto size_in_bytes = input_numel * input_type_size; - const auto block = 256; - const auto grid = (size_in_bytes + (block * block_size) - 1) / (block * block_size); - if (input.device().type() == at::kCPU) { - block_cipher_kernel_cpu_2(grid * block, cipher, block_size, + const auto total = (size_in_bytes + block_size - 1) / block_size; + block_cipher_kernel_cpu_2(total, cipher, block_size, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc ); } else if (input.device().type() == at::kCUDA) { #if defined(__CUDACC__) || defined(__HIPCC__) + const auto block = 256; + const auto grid = (size_in_bytes + (block * block_size) - 1) / (block * block_size); auto stream = at::cuda::getCurrentCUDAStream(); block_cipher_kernel_cuda_2<<>>(cipher, block_size, input_ptr, input_numel, input_type_size, input_index_calc, diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index def4d31..a1cb806 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -437,6 +437,7 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string block_cipher_2(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; + std::memset(&idx_block, 0, aes::block_t_size); *(reinterpret_cast(idx_block)) = idx; aes::encrypt(idx_block, key_bytes); for (size_t i = 0; i < aes::block_t_size; i++) { @@ -471,8 +472,9 @@ Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string ciphe block_cipher_2(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; + std::memset(&idx_block, 0, aes::block_t_size); *(reinterpret_cast(idx_block)) = idx; - aes::decrypt(idx_block, key_bytes); + aes::encrypt(idx_block, key_bytes); for (size_t i = 0; i < aes::block_t_size; i++) { block[i] ^= idx_block[i]; } From e4955f71fda61541a13dd0e5dadf55639e4761ab Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:16:37 -0500 Subject: [PATCH 03/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- test/test_csprng.py | 10 ++ torchcsprng/csrc/block_cipher.h | 251 +++++++++++++++++------------- torchcsprng/csrc/block_cipher_2.h | 174 --------------------- torchcsprng/csrc/csprng.h | 88 +++++++++-- 4 files changed, 227 insertions(+), 296 deletions(-) delete mode 100644 torchcsprng/csrc/block_cipher_2.h diff --git a/test/test_csprng.py b/test/test_csprng.py index 513d42d..3ed2b1e 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -69,6 +69,11 @@ def test_random_to_kstest(self): for dtype in self.num_dtypes: t = torch.zeros(self.size, dtype=dtype, device=device).random_(to_, generator=gen) res = stats.kstest(t.cpu(), stats.randint.cdf, args=(0, to_)) + # TODO REVERT! + # if res.statistic >= 0.1: + # print(t[:10]) + # print(dtype) + # print(res.statistic) self.assertTrue(res.statistic < 0.1) @unittest.skipIf(not torch.cuda.is_available() or not csprng.supports_cuda(), "CUDA is not available or csprng was not compiled with CUDA support") @@ -90,6 +95,11 @@ def test_random_from_to_kstest(self): if from_ < to_: t = torch.zeros(self.size, dtype=dtype, device=device).random_(from_, to_, generator=gen) res = stats.kstest(t.cpu(), stats.randint.cdf, args=(from_, to_)) + # TODO REVERT! + # if res.statistic >= 0.1: + # print(t[:10]) + # print(dtype) + # print(res.statistic) self.assertTrue(res.statistic < 0.2) @unittest.skipIf(not torch.cuda.is_available() or not csprng.supports_cuda(), "CUDA is not available or csprng was not compiled with CUDA support") diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 2ca313f..a612061 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -30,144 +30,181 @@ namespace torch { namespace csprng { -// Generates `block_t_size`-bytes random key Tensor on CPU -// using `generator`, which must be an instance of `at::CPUGeneratorImpl` -// and passes it to the `device`. -template -at::Tensor key_tensor(size_t block_t_size, c10::optional generator) { - std::lock_guard lock(generator->mutex()); - auto gen = at::check_generator(generator); - if (gen->key().defined()) { - return gen->key().clone(); - } - auto t = torch::empty({static_cast(block_t_size)}, torch::kUInt8); - using random_t = uint32_t; - constexpr size_t random_t_size = sizeof(random_t); - for (size_t i = 0; i < block_t_size / random_t_size; i++) { - const auto rand = gen->random(); - for (size_t j = 0; j < random_t_size; j++) { - size_t k = i * random_t_size + j; - t[k] = static_cast((rand >> (j * 8)) & 0xff); +template +TORCH_CSPRNG_HOST_DEVICE static void copy_input_to_block(int64_t idx, uint8_t* block, int block_size, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc) { + for (auto i = 0; i < block_size / input_type_size; ++i) { + const auto linear_index = idx * (block_size / input_type_size) + i; + if (linear_index < input_numel) { + std::memcpy( + &(block[i * input_type_size]), + &(reinterpret_cast(input_ptr)[input_index_calc(linear_index)]), + input_type_size + ); } } - return t; } -// A simple container for random state sub-blocks that implements RNG interface -// with random() and random64() methods, that are used by transformation function -template -struct RNGValues { - TORCH_CSPRNG_HOST_DEVICE RNGValues(uint64_t* vals) { - memcpy(&vals_, vals, size * sizeof(uint64_t)); - } - uint32_t TORCH_CSPRNG_HOST_DEVICE random() { auto res = static_cast(vals_[index]); index++; return res; } - uint64_t TORCH_CSPRNG_HOST_DEVICE random64() { auto res = vals_[index]; index++; return res; } -private: - uint64_t vals_[size]; - int index = 0; -}; - -// Runs a block cipher in a counter mode in approximately `numel / (block_t_size / sizeof(uint_t) / N)` CUDA threads, -// without any assumption about target tensor layout. It uses `index_calc` to find memory locations of -// the tensor elements. -// `scalar_t` is a scalar type equivalent of target tensor dtype -// `uint_t` is an unsigned integral type of sub-blocks that random state is divided to -// (e.g, 16 bytes random state block can be divided into 16 uint8_t sub-blocks -// or 8 uint16_t sub-block or 4 uint32_t sub-block or 2 uint64_t sub-blocks) -// `N` is a number of sub-block which is used by `transform_func` -// to generate a random value of specific distribution (e.g. `normal` uses 2) -// `numel` is a number of elements in target tensor -// `block_t_size` is a number of bytes in cipher's block (e.g. 16 for AES128) -// `cipher` is a callable that receives a counter `idx` and returns an encrypted block -// `transform_func` is a callable that converts N `uint_t` random state sub-blocks passed in RNGValues into target dtype `scalar_t` -template -TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper(int idx, scalar_t* data, int64_t numel, size_t block_t_size, cipher_t cipher, transform_t transform_func, index_calc_t index_calc) { - const int unroll_factor = block_t_size / sizeof(uint_t) / N; - if (unroll_factor * idx < numel) { - auto block = cipher(idx); - UNROLL_IF_CUDA - for (auto i = 0; i < unroll_factor; ++i) { - const auto li = unroll_factor * idx + i; - if (li < numel) { - uint64_t vals[N]; - UNROLL_IF_CUDA - for (size_t j = 0; j < N; j++) { - vals[j] = (reinterpret_cast(&block))[N * i + j]; - } - RNGValues rng(vals); - data[index_calc(li)] = transform_func(&rng); - } +template +TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* block, int block_size, int output_elem_per_block, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { +// std::cout << "output_elem_per_block = " << output_elem_per_block << std::endl; +// std::cout << "block_size = " << block_size << std::endl; +// std::cout << "output_type_size = " << output_type_size << std::endl; + for (auto i = 0; i < output_elem_per_block; ++i) { + const auto linear_index = idx * output_elem_per_block + i; + if (linear_index < output_numel) { + std::memcpy( + &(reinterpret_cast(output_ptr)[output_index_calc(linear_index)]), + &(block[i * output_type_size]), + output_type_size + ); } } } +template +TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper( + int64_t idx, cipher_t cipher, int block_size, int output_elem_per_block, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, + transform_t transform) { + uint8_t block[block_size]; + std::memset(&block, 0, block_size); // is it ok to use zeros as padding? + if (input_ptr != nullptr) { + copy_input_to_block(idx, block, block_size, input_ptr, input_numel, input_type_size, input_index_calc); + } + cipher(idx, block); + const auto new_block_size = transform(block); + copy_block_to_output(idx, block, new_block_size, output_elem_per_block, output_ptr, output_numel, output_type_size, output_index_calc); +} + #if defined(__CUDACC__) || defined(__HIPCC__) -template -__global__ static void block_cipher_kernel_cuda(scalar_t* data, int64_t numel, int block_t_size, cipher_t cipher, transform_t transform_func, index_calc_t index_calc) { +template +__global__ static void block_cipher_kernel_cuda(cipher_t cipher, int block_size, int output_elem_per_block, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, + transform_t transform) { const auto idx = blockIdx.x * blockDim.x + threadIdx.x; - block_cipher_kernel_helper(idx, data, numel, block_t_size, cipher, transform_func, index_calc); + block_cipher_kernel_helper(idx, cipher, block_size, output_elem_per_block + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform); } #endif -template -static void block_cipher_kernel_cpu_serial(int64_t begin, int64_t end, scalar_t* data, int64_t numel, int block_t_size, cipher_t cipher, transform_t transform_func, index_calc_t index_calc) { +template +static void block_cipher_kernel_cpu_serial(int64_t begin, int64_t end, cipher_t cipher, int block_size, int output_elem_per_block, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, + transform_t transform) { for (auto idx = begin; idx < end; ++idx) { - block_cipher_kernel_helper(idx, data, numel, block_t_size, cipher, transform_func, index_calc); + block_cipher_kernel_helper(idx, cipher, block_size, output_elem_per_block, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform); } } -template -static void block_cipher_kernel_cpu(int64_t total, scalar_t* data, int64_t numel, int block_t_size, cipher_t cipher, transform_t transform_func, index_calc_t index_calc) { +template +static void block_cipher_kernel_cpu(int64_t total, cipher_t cipher, int block_size, int output_elem_per_block, + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, + transform_t transform_func) { if (total < at::internal::GRAIN_SIZE || at::get_num_threads() == 1) { - block_cipher_kernel_cpu_serial(0, total, data, numel, block_t_size, cipher, transform_func, index_calc); + block_cipher_kernel_cpu_serial(0, total, cipher, block_size, output_elem_per_block, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform_func); } else { at::parallel_for(0, total, at::internal::GRAIN_SIZE, [&](int64_t begin, int64_t end) { - block_cipher_kernel_cpu_serial(begin, end, data, numel, block_t_size, cipher, transform_func, index_calc); + block_cipher_kernel_cpu_serial(begin, end, cipher, block_size, output_elem_per_block, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform_func); }); } } -// Runs a block cipher in a counter mode in approximately `numel / (block_t_size / sizeof(uint_t) / N)` CUDA threads. -// Each CUDA thread generates `block_t_size`-bytes random state and divides it into `block_t_size / sizeof(uint_t)` sub-blocks. -// Then `transform_func` transforms `N` random state sub-blocks passed in a `RNGValues` to final random values of type `scalar_t`. -template -void block_cipher_ctr_mode(at::TensorIterator& iter, int block_t_size, cipher_t cipher, transform_t transform_func) { - const auto numel = iter.numel(); - if (numel == 0) { - return; - } - const int unroll_factor = block_t_size / sizeof(uint_t) / N; - const auto block = 256; - const auto grid = (numel + (block * unroll_factor) - 1) / (block * unroll_factor); - scalar_t* data = (scalar_t*)iter.data_ptr(0); - auto offset_calc = make_offset_calculator<1>(iter); - auto index_calc_identity = [] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { return li; }; - auto index_calc_offset = [offset_calc] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { return offset_calc.get(li)[0] / sizeof(scalar_t); }; - if (iter.device_type() == at::kCPU) { - if (iter.output(0).is_contiguous()) { - block_cipher_kernel_cpu( - grid * block, data, numel, block_t_size, cipher, transform_func, index_calc_identity); - } else { - block_cipher_kernel_cpu( - grid * block, data, numel, block_t_size, cipher, transform_func, index_calc_offset); - } - } else if (iter.device_type() == at::kCUDA) { +template +void block_cipher( + void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, + void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, + Device device, cipher_t cipher, int block_size, int output_elem_per_block, transform_t transform_func) { +// if (input.numel() == 0) { +// return; +// } +// TORCH_CHECK((input_numel * input_type_size + block_size - 1) / block_size * block_size == output_numel * output_type_size, "wrong size"); + +// const auto size_in_bytes = input_numel * input_type_size; +// const auto size_in_bytes = output_numel * output_type_size; + + if (device.type() == at::kCPU) { +// const auto total = (size_in_bytes + block_size - 1) / block_size; +// const auto total = (size_in_bytes + block_size / N - 1) / block_size * N; + const auto total = (output_numel + output_elem_per_block - 1) / output_elem_per_block; + block_cipher_kernel_cpu(total, + cipher, block_size, output_elem_per_block, + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform_func + ); + } else if (device.type() == at::kCUDA) { #if defined(__CUDACC__) || defined(__HIPCC__) + const auto threads = 256; + const auto grid = (output_numel + (threads * output_elem_per_block) - 1) / (threads * output_elem_per_block); auto stream = at::cuda::getCurrentCUDAStream(); - if (iter.output(0).is_contiguous()) { - block_cipher_kernel_cuda<<>>( - data, numel, block_t_size, cipher, transform_func, index_calc_identity); - } else { - block_cipher_kernel_cuda<<>>( - data, numel, block_t_size, cipher, transform_func, index_calc_offset); - } + block_cipher_kernel_cuda<<>>( + cipher, block_size, output_elem_per_block + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + transform_func + ); AT_CUDA_CHECK(cudaGetLastError()); #else - TORCH_CHECK(false, "csprng was compiled without CUDA support"); + TORCH_CHECK(false, "torchcsprng was compiled without CUDA support"); #endif } else { - TORCH_CHECK(false, "block_cipher_ctr_mode supports only CPU and CUDA devices"); + TORCH_CHECK(false, "block_cipher supports only CPU and CUDA devices"); } } +std::function create_index_calc(Tensor input) { + if (input.is_contiguous()) { + const auto input_type_size = input.element_size(); + return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { + return li * input_type_size; + }; + } else { + const auto input_iter = TensorIterator::nullary_op(input); + const auto input_offset_calc = make_offset_calculator<1>(input_iter); + return [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { + return input_offset_calc.get(li)[0]; + }; + } +} + +template +void block_cipher(Tensor input, Tensor output, + cipher_t cipher, int block_size) { + + const auto input_ptr = input.data_ptr(); + const auto input_numel = input.numel(); + const auto input_type_size = input.element_size(); + const auto input_index_calc = create_index_calc(input); + + const auto output_ptr = output.data_ptr(); + const auto output_numel = output.numel(); + const auto output_type_size = output.element_size(); + const auto output_index_calc = create_index_calc(output); + + const auto device = output.device(); + + block_cipher( + input_ptr, input_numel, input_type_size, input_index_calc, + output_ptr, output_numel, output_type_size, output_index_calc, + device, cipher, block_size, block_size / output_type_size, + [block_size] (auto x) { return block_size; }); +} + }} diff --git a/torchcsprng/csrc/block_cipher_2.h b/torchcsprng/csrc/block_cipher_2.h deleted file mode 100644 index 0eca492..0000000 --- a/torchcsprng/csrc/block_cipher_2.h +++ /dev/null @@ -1,174 +0,0 @@ -/* - * Copyright (c) Facebook, Inc. and its affiliates. - * All rights reserved. - * - * This source code is licensed under the BSD-style license found in the - * LICENSE file in the root directory of this source tree. - */ - -#pragma once - -#include "macros.h" -#include -#include -#include "OffsetCalculator.cuh" -#include -#include -#include - -#if defined(__CUDACC__) || defined(__HIPCC__) -#include -#include -#endif - -#if defined(__CUDACC__) || defined(__HIPCC__) -#define UNROLL_IF_CUDA #pragma unroll -#else -#define UNROLL_IF_CUDA -#endif - -namespace torch { -namespace csprng { - -template -TORCH_CSPRNG_HOST_DEVICE static void copy_input_to_block(int64_t idx, uint8_t* block, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc) { - for (auto i = 0; i < block_size / input_type_size; ++i) { - const auto linear_index = idx * (block_size / input_type_size) + i; - if (linear_index < input_numel) { - std::memcpy( - &(block[i * input_type_size]), - &(reinterpret_cast(input_ptr)[input_index_calc(linear_index)]), - input_type_size - ); - } - } -} - -template -TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* block, int block_size, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - for (auto i = 0; i < block_size / output_type_size; ++i) { - const auto linear_index = idx * block_size / output_type_size + i; - if (linear_index < output_numel) { - std::memcpy( - &(reinterpret_cast(output_ptr)[output_index_calc(linear_index)]), - &(block[i * output_type_size]), - output_type_size - ); - } - } -} - -template -TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper_2(int64_t idx, cipher_t cipher, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - uint8_t block[block_size]; - memset(&block, 0, block_size); // is it ok to use zeros as padding? - copy_input_to_block(idx, block, block_size, input_ptr, input_numel, input_type_size, input_index_calc); - cipher(idx, block); - copy_block_to_output(idx, block, block_size, output_ptr, output_numel, output_type_size, output_index_calc); -} - -#if defined(__CUDACC__) || defined(__HIPCC__) -template -__global__ static void block_cipher_kernel_cuda_2(cipher_t cipher, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - const auto idx = blockIdx.x * blockDim.x + threadIdx.x; - block_cipher_kernel_helper_2(idx, cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc); -} -#endif - -template -static void block_cipher_kernel_cpu_serial_2(int64_t begin, int64_t end, cipher_t cipher, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - for (auto idx = begin; idx < end; ++idx) { - block_cipher_kernel_helper_2(idx, cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc); - } -} - -template -static void block_cipher_kernel_cpu_2(int64_t total, cipher_t cipher, int block_size, - void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, - void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { - if (total < at::internal::GRAIN_SIZE || at::get_num_threads() == 1) { - block_cipher_kernel_cpu_serial_2(0, total, cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc); - } else { - at::parallel_for(0, total, at::internal::GRAIN_SIZE, [&](int64_t begin, int64_t end) { - block_cipher_kernel_cpu_serial_2(begin, end, cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc); - }); - } -} - -template -void block_cipher_2(Tensor input, Tensor output, cipher_t cipher, int block_size) { - if (input.numel() == 0) { - return; - } - - const auto input_ptr = input.data_ptr(); - const auto input_numel = input.numel(); - const auto input_type_size = input.element_size(); - const auto input_iter = TensorIterator::nullary_op(input); - const auto input_offset_calc = make_offset_calculator<1>(input_iter); - const std::function input_index_calc_contiguous = [input_type_size] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? - return li * input_type_size; - }; - const std::function input_index_calc_non_contiguous = [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? - return input_offset_calc.get(li)[0]; - }; - const auto input_index_calc = input.is_contiguous() ? input_index_calc_contiguous : input_index_calc_non_contiguous; - - const auto output_ptr = output.data_ptr(); - const auto output_numel = output.numel(); - const auto output_type_size = output.element_size(); - const auto output_iter = TensorIterator::nullary_op(output); - const auto output_offset_calc = make_offset_calculator<1>(output_iter); - const std::function output_index_calc_contiguous = [output_type_size] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? - return li * output_type_size; - }; - const std::function output_index_calc_non_contiguous = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (int li) -> int { // TODO: int or uint32_t? - return output_offset_calc.get(li)[0]; - }; - const auto output_index_calc = output.is_contiguous() ? output_index_calc_contiguous : output_index_calc_non_contiguous; - - TORCH_CHECK((input_numel * input_type_size + block_size - 1) / block_size * block_size == output_numel * output_type_size, "wrong size"); - - const auto size_in_bytes = input_numel * input_type_size; - - if (input.device().type() == at::kCPU) { - const auto total = (size_in_bytes + block_size - 1) / block_size; - block_cipher_kernel_cpu_2(total, cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc - ); - } else if (input.device().type() == at::kCUDA) { -#if defined(__CUDACC__) || defined(__HIPCC__) - const auto block = 256; - const auto grid = (size_in_bytes + (block * block_size) - 1) / (block * block_size); - auto stream = at::cuda::getCurrentCUDAStream(); - block_cipher_kernel_cuda_2<<>>(cipher, block_size, - input_ptr, input_numel, input_type_size, input_index_calc, - output_ptr, output_numel, output_type_size, output_index_calc - ); - AT_CUDA_CHECK(cudaGetLastError()); -#else - TORCH_CHECK(false, "torchcsprng was compiled without CUDA support"); -#endif - } else { - TORCH_CHECK(false, "block_cipher supports only CPU and CUDA devices"); - } -} - -}} diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index a1cb806..96618c7 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -18,7 +18,6 @@ #include #include "macros.h" #include "block_cipher.h" -#include "block_cipher_2.h" #include "aes.h" #if defined(__CUDACC__) || defined(__HIPCC__) @@ -58,6 +57,29 @@ struct CSPRNGGeneratorImpl : public c10::GeneratorImpl { Tensor key_; }; +// Generates `block_t_size`-bytes random key Tensor on CPU +// using `generator`, which must be an instance of `at::CPUGeneratorImpl` +// and passes it to the `device`. +template +at::Tensor key_tensor(size_t block_t_size, c10::optional generator) { + std::lock_guard lock(generator->mutex()); + auto gen = at::check_generator(generator); + if (gen->key().defined()) { + return gen->key().clone(); + } + auto t = torch::empty({static_cast(block_t_size)}, torch::kUInt8); + using random_t = uint32_t; + constexpr size_t random_t_size = sizeof(random_t); + for (size_t i = 0; i < block_t_size / random_t_size; i++) { + const auto rand = gen->random(); + for (size_t j = 0; j < random_t_size; j++) { + size_t k = i * random_t_size + j; + t[k] = static_cast((rand >> (j * 8)) & 0xff); + } + } + return t; +} + template Tensor aes128_key_tensor(Generator generator) { return key_tensor(aes::block_t_size, generator); @@ -65,6 +87,20 @@ Tensor aes128_key_tensor(Generator generator) { // ==================================================================================================================== +// A simple container for random state sub-blocks that implements RNG interface +// with random() and random64() methods, that are used by transformation function +template +struct RNGValues { + TORCH_CSPRNG_HOST_DEVICE RNGValues(uint64_t* vals) { + memcpy(&vals_, vals, size * sizeof(uint64_t)); + } + uint32_t TORCH_CSPRNG_HOST_DEVICE random() { auto res = static_cast(vals_[index]); index++; return res; } + uint64_t TORCH_CSPRNG_HOST_DEVICE random64() { auto res = vals_[index]; index++; return res; } +private: + uint64_t vals_[size]; + int index = 0; +}; + // Applies AES in CTR mode with the `key` for passed TensorIterator iter. // `scalar_t` is a scalar type equivalent of target tensor dtype // `uint_t` is an unsigned integral type of sub-blocks that random state is divided to @@ -75,16 +111,38 @@ Tensor aes128_key_tensor(Generator generator) { // `key` is a CUDA pointer to random key memory block // `transform_func` is a callable that converts N `uint_t` random state sub-blocks passed in RNGValues into target dtype `scalar_t` template -void aes_helper(TensorIterator& iter, const uint8_t* key, transform_t transform_func) { - block_cipher_ctr_mode(iter, aes::block_t_size, - [key] TORCH_CSPRNG_HOST_DEVICE (unsigned int idx) -> aes::block_t { - aes::block_t block; - memset(&block, 0, aes::block_t_size); - block.x = idx; - aes::encrypt(reinterpret_cast(&block), key); - return block; +void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t transform_func) { + auto output = iter.tensor(0); + const auto index_calc = create_index_calc(output); + block_cipher( + nullptr, 0, 0, index_calc, + output.data_ptr(), output.numel(), output.element_size(), index_calc, + iter.device_type(), + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + uint8_t idx_block[aes::block_t_size]; + std::memset(&idx_block, 0, aes::block_t_size); + *(reinterpret_cast(idx_block)) = idx; + aes::encrypt(idx_block, key_bytes); + for (size_t i = 0; i < aes::block_t_size; i++) { + block[i] ^= idx_block[i]; + } }, - transform_func + aes::block_t_size, aes::block_t_size / (N * sizeof(uint_t)), + [transform_func] (auto block) { + const auto n = aes::block_t_size / (N * sizeof(uint_t)); +// std::cout << "N = " << N << std::endl; +// std::cout << "sizeof(uint_t) = " << sizeof(uint_t) << std::endl; +// std::cout << "n = " << n << std::endl; + for (size_t i = 0; i < n; ++i) { + uint64_t vals[N]; + for (size_t j = 0; j < N; ++j) { + vals[j] = (reinterpret_cast(block))[N * i + j]; + } + RNGValues rng(vals); + reinterpret_cast(block)[i] = transform_func(&rng); + } + return n * sizeof(uint_t); + } ); } @@ -152,7 +210,7 @@ struct RandomFromToKernel { std::is_same::value || std::is_same::value || std::is_same::value || - std::is_same::value) && range >= 1ULL << 32) + std::is_same::value)/* TODO: && range >= 1ULL << 32*/) { random_from_to_kernel_helper(iter, range, base, key); } else { @@ -427,14 +485,14 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string } const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher_2(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { aes::encrypt(block, key_bytes); }, aes::block_t_size ); } else if (mode == "ctr") { - block_cipher_2(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; std::memset(&idx_block, 0, aes::block_t_size); @@ -462,14 +520,14 @@ Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string ciphe } const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher_2(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { aes::decrypt(block, key_bytes); }, aes::block_t_size ); } else if (mode == "ctr") { - block_cipher_2(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; std::memset(&idx_block, 0, aes::block_t_size); From 583fb8025dcfbb78ec1dbd0f7938428d956514f4 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:21:22 -0500 Subject: [PATCH 04/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index a612061..d4415f3 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -155,7 +155,7 @@ void block_cipher( const auto grid = (output_numel + (threads * output_elem_per_block) - 1) / (threads * output_elem_per_block); auto stream = at::cuda::getCurrentCUDAStream(); block_cipher_kernel_cuda<<>>( - cipher, block_size, output_elem_per_block + cipher, block_size, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform_func From 66b2e5506fb3be6dc2ad006c73c3a9321227c711 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:39:32 -0500 Subject: [PATCH 05/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 53 ++++++++++++++++----------------- torchcsprng/csrc/csprng.h | 25 +++++++--------- 2 files changed, 35 insertions(+), 43 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index d4415f3..ba1e427 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -46,11 +46,8 @@ TORCH_CSPRNG_HOST_DEVICE static void copy_input_to_block(int64_t idx, uint8_t* b } template -TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* block, int block_size, int output_elem_per_block, +TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* block, int output_elem_per_block, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc) { -// std::cout << "output_elem_per_block = " << output_elem_per_block << std::endl; -// std::cout << "block_size = " << block_size << std::endl; -// std::cout << "output_type_size = " << output_type_size << std::endl; for (auto i = 0; i < output_elem_per_block; ++i) { const auto linear_index = idx * output_elem_per_block + i; if (linear_index < output_numel) { @@ -63,9 +60,9 @@ TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* } } -template +template TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper( - int64_t idx, cipher_t cipher, int block_size, int output_elem_per_block, + int64_t idx, cipher_t cipher, int output_elem_per_block, void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform) { @@ -75,50 +72,50 @@ TORCH_CSPRNG_HOST_DEVICE static void block_cipher_kernel_helper( copy_input_to_block(idx, block, block_size, input_ptr, input_numel, input_type_size, input_index_calc); } cipher(idx, block); - const auto new_block_size = transform(block); - copy_block_to_output(idx, block, new_block_size, output_elem_per_block, output_ptr, output_numel, output_type_size, output_index_calc); + transform(block); + copy_block_to_output(idx, block, output_elem_per_block, output_ptr, output_numel, output_type_size, output_index_calc); } #if defined(__CUDACC__) || defined(__HIPCC__) -template -__global__ static void block_cipher_kernel_cuda(cipher_t cipher, int block_size, int output_elem_per_block, +template +__global__ static void block_cipher_kernel_cuda(cipher_t cipher, int output_elem_per_block, void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform) { const auto idx = blockIdx.x * blockDim.x + threadIdx.x; - block_cipher_kernel_helper(idx, cipher, block_size, output_elem_per_block + block_cipher_kernel_helper(idx, cipher, output_elem_per_block input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform); } #endif -template -static void block_cipher_kernel_cpu_serial(int64_t begin, int64_t end, cipher_t cipher, int block_size, int output_elem_per_block, +template +static void block_cipher_kernel_cpu_serial(int64_t begin, int64_t end, cipher_t cipher, int output_elem_per_block, void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform) { for (auto idx = begin; idx < end; ++idx) { - block_cipher_kernel_helper(idx, cipher, block_size, output_elem_per_block, + block_cipher_kernel_helper(idx, cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform); } } -template -static void block_cipher_kernel_cpu(int64_t total, cipher_t cipher, int block_size, int output_elem_per_block, +template +static void block_cipher_kernel_cpu(int64_t total, cipher_t cipher, int output_elem_per_block, void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform_func) { if (total < at::internal::GRAIN_SIZE || at::get_num_threads() == 1) { - block_cipher_kernel_cpu_serial(0, total, cipher, block_size, output_elem_per_block, + block_cipher_kernel_cpu_serial(0, total, cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform_func); } else { at::parallel_for(0, total, at::internal::GRAIN_SIZE, [&](int64_t begin, int64_t end) { - block_cipher_kernel_cpu_serial(begin, end, cipher, block_size, output_elem_per_block, + block_cipher_kernel_cpu_serial(begin, end, cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform_func); @@ -126,11 +123,11 @@ static void block_cipher_kernel_cpu(int64_t total, cipher_t cipher, int block_si } } -template +template void block_cipher( void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, - Device device, cipher_t cipher, int block_size, int output_elem_per_block, transform_t transform_func) { + Device device, cipher_t cipher, int output_elem_per_block, transform_t transform_func) { // if (input.numel() == 0) { // return; // } @@ -143,8 +140,8 @@ void block_cipher( // const auto total = (size_in_bytes + block_size - 1) / block_size; // const auto total = (size_in_bytes + block_size / N - 1) / block_size * N; const auto total = (output_numel + output_elem_per_block - 1) / output_elem_per_block; - block_cipher_kernel_cpu(total, - cipher, block_size, output_elem_per_block, + block_cipher_kernel_cpu(total, + cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform_func @@ -154,7 +151,7 @@ void block_cipher( const auto threads = 256; const auto grid = (output_numel + (threads * output_elem_per_block) - 1) / (threads * output_elem_per_block); auto stream = at::cuda::getCurrentCUDAStream(); - block_cipher_kernel_cuda<<>>( + block_cipher_kernel_cuda<<>>( cipher, block_size, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, @@ -184,9 +181,9 @@ std::function create_index_calc(Tensor input) { } } -template +template void block_cipher(Tensor input, Tensor output, - cipher_t cipher, int block_size) { + cipher_t cipher) { const auto input_ptr = input.data_ptr(); const auto input_numel = input.numel(); @@ -200,11 +197,11 @@ void block_cipher(Tensor input, Tensor output, const auto device = output.device(); - block_cipher( + block_cipher( input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, - device, cipher, block_size, block_size / output_type_size, - [block_size] (auto x) { return block_size; }); + device, cipher, block_size / output_type_size, + [] (auto x) {}); } }} diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 96618c7..2752d1a 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -114,7 +114,7 @@ template void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t transform_func) { auto output = iter.tensor(0); const auto index_calc = create_index_calc(output); - block_cipher( + block_cipher( nullptr, 0, 0, index_calc, output.data_ptr(), output.numel(), output.element_size(), index_calc, iter.device_type(), @@ -127,7 +127,7 @@ void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t tran block[i] ^= idx_block[i]; } }, - aes::block_t_size, aes::block_t_size / (N * sizeof(uint_t)), + aes::block_t_size / (N * sizeof(uint_t)), [transform_func] (auto block) { const auto n = aes::block_t_size / (N * sizeof(uint_t)); // std::cout << "N = " << N << std::endl; @@ -141,7 +141,6 @@ void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t tran RNGValues rng(vals); reinterpret_cast(block)[i] = transform_func(&rng); } - return n * sizeof(uint_t); } ); } @@ -485,14 +484,13 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string } const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { aes::encrypt(block, key_bytes); - }, - aes::block_t_size + } ); } else if (mode == "ctr") { - block_cipher(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; std::memset(&idx_block, 0, aes::block_t_size); @@ -501,8 +499,7 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string for (size_t i = 0; i < aes::block_t_size; i++) { block[i] ^= idx_block[i]; } - }, - aes::block_t_size + } ); } else { TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); @@ -520,14 +517,13 @@ Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string ciphe } const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { aes::decrypt(block, key_bytes); - }, - aes::block_t_size + } ); } else if (mode == "ctr") { - block_cipher(input, output, + block_cipher(input, output, [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; std::memset(&idx_block, 0, aes::block_t_size); @@ -536,8 +532,7 @@ Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string ciphe for (size_t i = 0; i < aes::block_t_size; i++) { block[i] ^= idx_block[i]; } - }, - aes::block_t_size + } ); } else { TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); From 6bd00308e7f24e9ce1b95c21989238932dd37b07 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:42:53 -0500 Subject: [PATCH 06/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index ba1e427..62bb9a6 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -151,7 +151,7 @@ void block_cipher( const auto threads = 256; const auto grid = (output_numel + (threads * output_elem_per_block) - 1) / (threads * output_elem_per_block); auto stream = at::cuda::getCurrentCUDAStream(); - block_cipher_kernel_cuda<<>>( + block_cipher_kernel_cuda<<>>( cipher, block_size, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, From 7465ef10dde96fce81e039509f507bcce4dcb0a3 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:48:32 -0500 Subject: [PATCH 07/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 62bb9a6..f1d9b2d 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -152,7 +152,7 @@ void block_cipher( const auto grid = (output_numel + (threads * output_elem_per_block) - 1) / (threads * output_elem_per_block); auto stream = at::cuda::getCurrentCUDAStream(); block_cipher_kernel_cuda<<>>( - cipher, block_size, output_elem_per_block, + cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform_func From 247ca74ad46dfb7f066fa85c966edee1104e2b8f Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Tue, 17 Nov 2020 23:50:52 -0500 Subject: [PATCH 08/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index f1d9b2d..631ffe4 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -83,7 +83,7 @@ __global__ static void block_cipher_kernel_cuda(cipher_t cipher, int output_elem void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform) { const auto idx = blockIdx.x * blockDim.x + threadIdx.x; - block_cipher_kernel_helper(idx, cipher, output_elem_per_block + block_cipher_kernel_helper(idx, cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform); From f6a260a405de33a648c5b94a18214bf0f31de597 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 00:00:40 -0500 Subject: [PATCH 09/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- torchcsprng/csrc/csprng.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 631ffe4..6db2cd5 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -201,7 +201,7 @@ void block_cipher(Tensor input, Tensor output, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, device, cipher, block_size / output_type_size, - [] (auto x) {}); + [] TORCH_CSPRNG_HOST_DEVICE (auto x) {}); } }} diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 2752d1a..977b742 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -128,7 +128,7 @@ void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t tran } }, aes::block_t_size / (N * sizeof(uint_t)), - [transform_func] (auto block) { + [transform_func] TORCH_CSPRNG_HOST_DEVICE (auto block) { const auto n = aes::block_t_size / (N * sizeof(uint_t)); // std::cout << "N = " << N << std::endl; // std::cout << "sizeof(uint_t) = " << sizeof(uint_t) << std::endl; From 9cbd83f64bc512d8ddee7ded5030428dda576b40 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 00:06:58 -0500 Subject: [PATCH 10/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- torchcsprng/csrc/csprng.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 6db2cd5..9b9aecf 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -201,7 +201,7 @@ void block_cipher(Tensor input, Tensor output, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, device, cipher, block_size / output_type_size, - [] TORCH_CSPRNG_HOST_DEVICE (auto x) {}); + [] TORCH_CSPRNG_HOST_DEVICE (uint8_t* x) {}); } }} diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 977b742..23d2481 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -128,7 +128,7 @@ void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t tran } }, aes::block_t_size / (N * sizeof(uint_t)), - [transform_func] TORCH_CSPRNG_HOST_DEVICE (auto block) { + [transform_func] TORCH_CSPRNG_HOST_DEVICE (uint8_t* block) { const auto n = aes::block_t_size / (N * sizeof(uint_t)); // std::cout << "N = " << N << std::endl; // std::cout << "sizeof(uint_t) = " << sizeof(uint_t) << std::endl; From 5ae1104ac6b84025c6ac1a7a16eac6b8e677183d Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 00:11:30 -0500 Subject: [PATCH 11/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 9b9aecf..bb1926e 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -83,7 +83,7 @@ __global__ static void block_cipher_kernel_cuda(cipher_t cipher, int output_elem void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, transform_t transform) { const auto idx = blockIdx.x * blockDim.x + threadIdx.x; - block_cipher_kernel_helper(idx, cipher, output_elem_per_block, + block_cipher_kernel_helper(idx, cipher, output_elem_per_block, input_ptr, input_numel, input_type_size, input_index_calc, output_ptr, output_numel, output_type_size, output_index_calc, transform); From 1ea40900d4707f75a5f9cd7c4b9c5b6d93e5896f Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 00:28:43 -0500 Subject: [PATCH 12/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index bb1926e..290d3a3 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -166,7 +166,7 @@ void block_cipher( } } -std::function create_index_calc(Tensor input) { +std::function create_index_calc(Tensor input) { if (input.is_contiguous()) { const auto input_type_size = input.element_size(); return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { From a04096419a718177cbc0c35c305cd0a6eadc238c Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 16:26:04 -0500 Subject: [PATCH 13/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 22 ++++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 290d3a3..524e0c4 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -128,9 +128,9 @@ void block_cipher( void* input_ptr, int64_t input_numel, int input_type_size, input_index_calc_t input_index_calc, void* output_ptr, int64_t output_numel, int output_type_size, output_index_calc_t output_index_calc, Device device, cipher_t cipher, int output_elem_per_block, transform_t transform_func) { -// if (input.numel() == 0) { -// return; -// } + if (output_ptr == nullptr || output_numel == 0) { + return; + } // TORCH_CHECK((input_numel * input_type_size + block_size - 1) / block_size * block_size == output_numel * output_type_size, "wrong size"); // const auto size_in_bytes = input_numel * input_type_size; @@ -182,16 +182,26 @@ std::function create_index_calc(Tensor input) } template -void block_cipher(Tensor input, Tensor output, - cipher_t cipher) { - +void block_cipher(Tensor input, Tensor output, cipher_t cipher) { const auto input_ptr = input.data_ptr(); const auto input_numel = input.numel(); + + // Otherwise OffsetCalculator/IntDivider crashes with integer division by zero + if (input_ptr == nullptr || input_numel == 0) { + return; + } + const auto input_type_size = input.element_size(); const auto input_index_calc = create_index_calc(input); const auto output_ptr = output.data_ptr(); const auto output_numel = output.numel(); + + // Otherwise OffsetCalculator/IntDivider crashes with integer division by zero + if (output_ptr == nullptr || output_numel == 0) { + return; + } + const auto output_type_size = output.element_size(); const auto output_index_calc = create_index_calc(output); From 2ae9d3e663897d768849362205393cca64fbb434 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 16:34:31 -0500 Subject: [PATCH 14/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 524e0c4..2b75e7f 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -166,19 +166,19 @@ void block_cipher( } } -std::function create_index_calc(Tensor input) { - if (input.is_contiguous()) { - const auto input_type_size = input.element_size(); - return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { - return li * input_type_size; - }; - } else { +auto create_index_calc(Tensor input) { +// if (input.is_contiguous()) { +// const auto input_type_size = input.element_size(); +// return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { +// return li * input_type_size; +// }; +// } else { const auto input_iter = TensorIterator::nullary_op(input); const auto input_offset_calc = make_offset_calculator<1>(input_iter); return [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { return input_offset_calc.get(li)[0]; }; - } +// } } template From cb7d77be20b24807d2b3b77864ce88da792f9c81 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 17:22:53 -0500 Subject: [PATCH 15/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 35 +++++++++++++++++++-------------- torchcsprng/csrc/csprng.h | 9 ++++++--- 2 files changed, 26 insertions(+), 18 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 2b75e7f..0d8575c 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -166,20 +166,19 @@ void block_cipher( } } -auto create_index_calc(Tensor input) { -// if (input.is_contiguous()) { -// const auto input_type_size = input.element_size(); -// return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { -// return li * input_type_size; +//auto create_index_calc(Tensor input) { +//// if (input.is_contiguous()) { +//// const auto input_type_size = input.element_size(); +//// return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { +//// return li * input_type_size; +//// }; +//// } else { +// const auto input_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(input)); +// return [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { +// return input_offset_calc.get(li)[0]; // }; -// } else { - const auto input_iter = TensorIterator::nullary_op(input); - const auto input_offset_calc = make_offset_calculator<1>(input_iter); - return [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { - return input_offset_calc.get(li)[0]; - }; -// } -} +//// } +//} template void block_cipher(Tensor input, Tensor output, cipher_t cipher) { @@ -192,7 +191,10 @@ void block_cipher(Tensor input, Tensor output, cipher_t cipher) { } const auto input_type_size = input.element_size(); - const auto input_index_calc = create_index_calc(input); + const auto input_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(input)); + const auto input_index_calc = [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { + return input_offset_calc.get(li)[0]; + }; const auto output_ptr = output.data_ptr(); const auto output_numel = output.numel(); @@ -203,7 +205,10 @@ void block_cipher(Tensor input, Tensor output, cipher_t cipher) { } const auto output_type_size = output.element_size(); - const auto output_index_calc = create_index_calc(output); + const auto output_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(output)); + const auto output_index_calc = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { + return output_offset_calc.get(li)[0]; + }; const auto device = output.device(); diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 23d2481..a2c993d 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -113,10 +113,13 @@ struct RNGValues { template void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t transform_func) { auto output = iter.tensor(0); - const auto index_calc = create_index_calc(output); + const auto output_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(output)); + const auto output_index_calc = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { + return output_offset_calc.get(li)[0]; + }; block_cipher( - nullptr, 0, 0, index_calc, - output.data_ptr(), output.numel(), output.element_size(), index_calc, + nullptr, 0, 0, output_index_calc, + output.data_ptr(), output.numel(), output.element_size(), output_index_calc, iter.device_type(), [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { uint8_t idx_block[aes::block_t_size]; From fb23aae726498b53d647cf2377f5883957f537a2 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 19:28:01 -0500 Subject: [PATCH 16/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- test/test_csprng.py | 4 ++-- torchcsprng/csrc/csprng.h | 5 +---- 2 files changed, 3 insertions(+), 6 deletions(-) diff --git a/test/test_csprng.py b/test/test_csprng.py index 3ed2b1e..b19a811 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -392,8 +392,8 @@ def sizeof(dtype): encrypted = torch.empty(encrypted_size, dtype=encrypted_dtype, device=device).random_() decrypted = torch.empty(decrypted_size, dtype=decrypted_dtype, device=device).random_() - initial_np = initial.numpy().view(np.int8) - decrypted_np = decrypted.numpy().view(np.int8) + initial_np = initial.cpu().numpy().view(np.int8) + decrypted_np = decrypted.cpu().numpy().view(np.int8) padding_size_bytes = initial_size * sizeof(initial_dtype) - decrypted_size * sizeof(decrypted_dtype) if padding_size_bytes != 0: decrypted_np = decrypted_np[:padding_size_bytes] diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index a2c993d..1cf03be 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -112,7 +112,7 @@ struct RNGValues { // `transform_func` is a callable that converts N `uint_t` random state sub-blocks passed in RNGValues into target dtype `scalar_t` template void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t transform_func) { - auto output = iter.tensor(0); + const auto output = iter.tensor(0); const auto output_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(output)); const auto output_index_calc = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { return output_offset_calc.get(li)[0]; @@ -133,9 +133,6 @@ void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t tran aes::block_t_size / (N * sizeof(uint_t)), [transform_func] TORCH_CSPRNG_HOST_DEVICE (uint8_t* block) { const auto n = aes::block_t_size / (N * sizeof(uint_t)); -// std::cout << "N = " << N << std::endl; -// std::cout << "sizeof(uint_t) = " << sizeof(uint_t) << std::endl; -// std::cout << "n = " << n << std::endl; for (size_t i = 0; i < n; ++i) { uint64_t vals[N]; for (size_t j = 0; j < N; ++j) { From fa7970d2cecc93c6a4b1050fd73d770a731c3c81 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 19:31:29 -0500 Subject: [PATCH 17/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/csprng.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 1cf03be..56bb818 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -112,7 +112,7 @@ struct RNGValues { // `transform_func` is a callable that converts N `uint_t` random state sub-blocks passed in RNGValues into target dtype `scalar_t` template void aes_helper(TensorIterator& iter, const uint8_t* key_bytes, transform_t transform_func) { - const auto output = iter.tensor(0); + auto output = iter.tensor(0); const auto output_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(output)); const auto output_index_calc = [output_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { return output_offset_calc.get(li)[0]; From caefc3438b030a32e1378b0880981eda8a5521ab Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 20:17:07 -0500 Subject: [PATCH 18/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- test/test_csprng.py | 3 +++ torchcsprng/csrc/block_cipher.h | 14 -------------- 2 files changed, 3 insertions(+), 14 deletions(-) diff --git a/test/test_csprng.py b/test/test_csprng.py index b19a811..78e5438 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -404,6 +404,9 @@ def sizeof(dtype): self.assertFalse(np.array_equal(initial_np, decrypted_np)) csprng.decrypt(encrypted, decrypted, key, "aes128", mode) + decrypted_np = decrypted.cpu().numpy().view(np.int8) + if padding_size_bytes != 0: + decrypted_np = decrypted_np[:padding_size_bytes] self.assertTrue(np.array_equal(initial_np, decrypted_np)) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index 0d8575c..e3822e5 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -166,20 +166,6 @@ void block_cipher( } } -//auto create_index_calc(Tensor input) { -//// if (input.is_contiguous()) { -//// const auto input_type_size = input.element_size(); -//// return [input_type_size] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { -//// return li * input_type_size; -//// }; -//// } else { -// const auto input_offset_calc = make_offset_calculator<1>(TensorIterator::nullary_op(input)); -// return [input_offset_calc] TORCH_CSPRNG_HOST_DEVICE (uint32_t li) -> uint32_t { -// return input_offset_calc.get(li)[0]; -// }; -//// } -//} - template void block_cipher(Tensor input, Tensor output, cipher_t cipher) { const auto input_ptr = input.data_ptr(); From 71e00c328428cbe344db4835ca324ec5e2d0a72e Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 20:34:08 -0500 Subject: [PATCH 19/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- test/test_csprng.py | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/test/test_csprng.py b/test/test_csprng.py index 78e5438..21f0642 100644 --- a/test/test_csprng.py +++ b/test/test_csprng.py @@ -69,11 +69,6 @@ def test_random_to_kstest(self): for dtype in self.num_dtypes: t = torch.zeros(self.size, dtype=dtype, device=device).random_(to_, generator=gen) res = stats.kstest(t.cpu(), stats.randint.cdf, args=(0, to_)) - # TODO REVERT! - # if res.statistic >= 0.1: - # print(t[:10]) - # print(dtype) - # print(res.statistic) self.assertTrue(res.statistic < 0.1) @unittest.skipIf(not torch.cuda.is_available() or not csprng.supports_cuda(), "CUDA is not available or csprng was not compiled with CUDA support") @@ -95,11 +90,6 @@ def test_random_from_to_kstest(self): if from_ < to_: t = torch.zeros(self.size, dtype=dtype, device=device).random_(from_, to_, generator=gen) res = stats.kstest(t.cpu(), stats.randint.cdf, args=(from_, to_)) - # TODO REVERT! - # if res.statistic >= 0.1: - # print(t[:10]) - # print(dtype) - # print(res.statistic) self.assertTrue(res.statistic < 0.2) @unittest.skipIf(not torch.cuda.is_available() or not csprng.supports_cuda(), "CUDA is not available or csprng was not compiled with CUDA support") From 9469ece8e16c1bd67557b1120634aea998fe45ed Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 21:06:10 -0500 Subject: [PATCH 20/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/csprng.h | 86 +++++++++++++++++++++------------------ 1 file changed, 46 insertions(+), 40 deletions(-) diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 56bb818..cf9fe0d 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -474,33 +474,57 @@ Tensor& randperm_generator_out(Tensor& result, int64_t n, c10::optional(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + aes::encrypt(block, key_bytes); + } + ); +} + +void aes_ecb_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { + block_cipher(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + aes::decrypt(block, key_bytes); + } + ); +} + +void aes_ctr_encrypt(Tensor input, Tensor output, uint8_t* key_bytes) { + block_cipher(input, output, + [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { + uint8_t idx_block[aes::block_t_size]; + std::memset(&idx_block, 0, aes::block_t_size); + *(reinterpret_cast(idx_block)) = idx; + aes::encrypt(idx_block, key_bytes); + for (size_t i = 0; i < aes::block_t_size; i++) { + block[i] ^= idx_block[i]; + } + } + ); +} + +void aes_ctr_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { + aes_ctr_encrypt(input, output, key_bytes); +} + +// Let's assume that input and output have integral dtype, so there is no transform for now. +Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { +// TORCH_CHECK(input.numel() * input.itemsize() == output.numel() * output.itemsize(), "input and output tensors must have the same size in byte"); + check_cipher(cipher, key); const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher(input, output, - [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { - aes::encrypt(block, key_bytes); - } - ); + aes_ecb_encrypt(input, output, key_bytes); } else if (mode == "ctr") { - block_cipher(input, output, - [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { - uint8_t idx_block[aes::block_t_size]; - std::memset(&idx_block, 0, aes::block_t_size); - *(reinterpret_cast(idx_block)) = idx; - aes::encrypt(idx_block, key_bytes); - for (size_t i = 0; i < aes::block_t_size; i++) { - block[i] ^= idx_block[i]; - } - } - ); + aes_ctr_encrypt(input, output, key_bytes); } else { TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); } @@ -510,30 +534,12 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { // TORCH_CHECK(input.numel() * input.itemsize() == output.numel() * output.itemsize(), "input and output tensors must have the same size in byte"); - if (cipher == "aes128") { - TORCH_CHECK(key.element_size() * key.numel() == 16, "key tensor must have 16 bytes(128 bits)"); - } else { - TORCH_CHECK(false, "encrypt/decrypt supports \"aes128\" cipher, \"", cipher, "\" is not supported."); - } + check_cipher(cipher, key); const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { - block_cipher(input, output, - [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { - aes::decrypt(block, key_bytes); - } - ); + aes_ecb_decrypt(input, output, key_bytes); } else if (mode == "ctr") { - block_cipher(input, output, - [key_bytes] TORCH_CSPRNG_HOST_DEVICE (int64_t idx, uint8_t* block) -> void { - uint8_t idx_block[aes::block_t_size]; - std::memset(&idx_block, 0, aes::block_t_size); - *(reinterpret_cast(idx_block)) = idx; - aes::encrypt(idx_block, key_bytes); - for (size_t i = 0; i < aes::block_t_size; i++) { - block[i] ^= idx_block[i]; - } - } - ); + aes_ctr_decrypt(input, output, key_bytes); } else { TORCH_CHECK(false, "encrypt/decrypt supports \"ecb\" and \"ctr\" modes, \"", mode, "\" is not supported."); } From 8b01c563dd229b763c5b85faef696bb9a4d05ab2 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 21:35:13 -0500 Subject: [PATCH 21/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/aes.h | 10 +--------- torchcsprng/csrc/csprng.h | 13 +++++++++++-- 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/torchcsprng/csrc/aes.h b/torchcsprng/csrc/aes.h index bd41928..c4ece07 100644 --- a/torchcsprng/csrc/aes.h +++ b/torchcsprng/csrc/aes.h @@ -63,15 +63,7 @@ namespace aes { #define Nr 10 // The number of rounds in AES Cipher. #endif -#if !defined(__CUDACC__) && !defined(__HIPCC__) -struct ulonglong2 // TODO: should have something like `__builtin_align__(16)` -{ - unsigned long long int x, y; -}; -#endif - -typedef ulonglong2 block_t; -constexpr size_t block_t_size = sizeof(block_t); +constexpr size_t block_t_size = 16; typedef uint8_t state_t[4][4]; diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index cf9fe0d..21924db 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -518,7 +518,13 @@ void aes_ctr_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { -// TORCH_CHECK(input.numel() * input.itemsize() == output.numel() * output.itemsize(), "input and output tensors must have the same size in byte"); + const auto output_size_bytes = output.numel() * output.itemsize(); + const auto input_size_bytes = input.numel() * input.itemsize(); + const auto input_size_bytes_rounded = (input_size_bytes + aes::block_t_size - 1) / aes::block_t_size * aes::block_t_size; + TORCH_CHECK(output_size_bytes == input_size_bytes_rounded, + "output size in bytes(", output_size_bytes, + ") is not equal to input size in bytes rounded to block size(", + input_size_bytes_rounded, ")"); check_cipher(cipher, key); const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { @@ -533,7 +539,10 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { -// TORCH_CHECK(input.numel() * input.itemsize() == output.numel() * output.itemsize(), "input and output tensors must have the same size in byte"); + const auto output_size_bytes = output.numel() * output.itemsize(); + const auto input_size_bytes = input.numel() * input.itemsize(); + TORCH_CHECK(output_size_bytes == input_size_bytes, "input and output tensors must have the same size in byte"); + TORCH_CHECK(input_size_bytes % aes::block_t_size == 0, "input tensor size in bytes must divisible by cipher block size in bytes without reminder"); check_cipher(cipher, key); const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { From 7f91368fa3d8db1b6e4769e9a9c1aa77255e7b2b Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 21:38:08 -0500 Subject: [PATCH 22/26] Update on "encrypt/decrypt" [ghstack-poisoned] --- torchcsprng/csrc/csprng.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 21924db..c59fb23 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -542,7 +542,7 @@ Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string ciphe const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize(); TORCH_CHECK(output_size_bytes == input_size_bytes, "input and output tensors must have the same size in byte"); - TORCH_CHECK(input_size_bytes % aes::block_t_size == 0, "input tensor size in bytes must divisible by cipher block size in bytes without reminder"); + TORCH_CHECK(input_size_bytes % aes::block_t_size == 0, "input tensor size in bytes must divisible by cipher block size in bytes"); check_cipher(cipher, key); const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { From 5d9c1c75c54b786f38332d47d72f8d746188017e Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 22:41:18 -0500 Subject: [PATCH 23/26] Update on "torchcsprng.encrypt/torchcsprng.decrypt with AES128 ECB/CTR support" This PR introduces two new methods to `torchcsprng` module: * `torchcsprng.encrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype and size in bytes(zero-padding is used to make its size in bytes divisible by block size in bytes) > - `output` tensor can have any dtype and the same device as `input` tensor and the size in bytes rounded to the block size in bytes(16 bytes for AES 128) > - `key` tensor can be any CPU or CUDA tensor of any dtype and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) * `torchcsprng.decrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype with size in bytes divisible by the block size in bytes(16 bytes for AES 128) > - `output` tensor can have any dtype but the same device as `input` tensor and the same size in bytes as `input` tensor > - `key` tensor can be any CPU or CUDA tensor of any dtype and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) Also this PR unifies encryption/decryption with existing random number generation which uses AES128 in CTR mode Fixes #77 [ghstack-poisoned] --- torchcsprng/csrc/csprng.h | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index c59fb23..4c50eb2 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -518,6 +518,7 @@ void aes_ctr_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { + TORCH_CHECK(input.device() == output.device(), "input and output tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize(); const auto input_size_bytes_rounded = (input_size_bytes + aes::block_t_size - 1) / aes::block_t_size * aes::block_t_size; @@ -526,7 +527,7 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string ") is not equal to input size in bytes rounded to block size(", input_size_bytes_rounded, ")"); check_cipher(cipher, key); - const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); + const auto key_bytes = reinterpret_cast(key.cpu().contiguous().data_ptr()); if (mode == "ecb") { aes_ecb_encrypt(input, output, key_bytes); } else if (mode == "ctr") { @@ -539,12 +540,13 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { + TORCH_CHECK(input.device() == output.device(), "input and output tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize(); TORCH_CHECK(output_size_bytes == input_size_bytes, "input and output tensors must have the same size in byte"); TORCH_CHECK(input_size_bytes % aes::block_t_size == 0, "input tensor size in bytes must divisible by cipher block size in bytes"); check_cipher(cipher, key); - const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); + const auto key_bytes = reinterpret_cast(key.cpu().contiguous().data_ptr()); if (mode == "ecb") { aes_ecb_decrypt(input, output, key_bytes); } else if (mode == "ctr") { From c1c75bba4908c7120b74217a402a18510b48796e Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Wed, 18 Nov 2020 22:48:33 -0500 Subject: [PATCH 24/26] Update on "torchcsprng.encrypt/torchcsprng.decrypt with AES128 ECB/CTR support" This PR introduces two new methods to `torchcsprng` module: * `torchcsprng.encrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype and size in bytes(zero-padding is used to make its size in bytes divisible by block size in bytes) > - `output` tensor can have any dtype and the same device as `input` tensor and the size in bytes rounded to the block size in bytes(16 bytes for AES 128) > - `key` tensor can be any CPU or CUDA tensor of any dtype and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) * `torchcsprng.decrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype with size in bytes divisible by the block size in bytes(16 bytes for AES 128) > - `output` tensor can have any dtype but the same device as `input` tensor and the same size in bytes as `input` tensor > - `key` tensor can be any CPU or CUDA tensor of any dtype and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) Also this PR unifies encryption/decryption with existing random number generation which uses AES128 in CTR mode Fixes #77 [ghstack-poisoned] --- torchcsprng/csrc/csprng.h | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 4c50eb2..57c4e54 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -518,7 +518,7 @@ void aes_ctr_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { - TORCH_CHECK(input.device() == output.device(), "input and output tensors must have the same device"); + TORCH_CHECK(input.device() == output.device() && input.device() == key.device(), "input, output and key tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize(); const auto input_size_bytes_rounded = (input_size_bytes + aes::block_t_size - 1) / aes::block_t_size * aes::block_t_size; @@ -527,7 +527,7 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string ") is not equal to input size in bytes rounded to block size(", input_size_bytes_rounded, ")"); check_cipher(cipher, key); - const auto key_bytes = reinterpret_cast(key.cpu().contiguous().data_ptr()); + const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { aes_ecb_encrypt(input, output, key_bytes); } else if (mode == "ctr") { @@ -540,13 +540,13 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string // Let's assume that input and output have integral dtype, so there is no transform for now. Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { - TORCH_CHECK(input.device() == output.device(), "input and output tensors must have the same device"); + TORCH_CHECK(input.device() == output.device() && input.device() == key.device(), "input, output and key tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize(); TORCH_CHECK(output_size_bytes == input_size_bytes, "input and output tensors must have the same size in byte"); TORCH_CHECK(input_size_bytes % aes::block_t_size == 0, "input tensor size in bytes must divisible by cipher block size in bytes"); check_cipher(cipher, key); - const auto key_bytes = reinterpret_cast(key.cpu().contiguous().data_ptr()); + const auto key_bytes = reinterpret_cast(key.contiguous().data_ptr()); if (mode == "ecb") { aes_ecb_decrypt(input, output, key_bytes); } else if (mode == "ctr") { From c45ff91962cdc0022202d6ba5ffe03391e841288 Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Thu, 19 Nov 2020 17:45:01 -0500 Subject: [PATCH 25/26] Update on "torchcsprng.encrypt/torchcsprng.decrypt with AES128 ECB/CTR support" This PR introduces two new methods to `torchcsprng` module: * `torchcsprng.encrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype and size in bytes(zero-padding is used to make its size in bytes divisible by block size in bytes) > - `output` tensor can have any dtype and the same device as `input` tensor and the size in bytes rounded to the block size in bytes(16 bytes for AES 128) > - `key` tensor can have any dtype and the same device as `input` tensor and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) * `torchcsprng.decrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype with size in bytes divisible by the block size in bytes(16 bytes for AES 128) > - `output` tensor can have any dtype but the same device as `input` tensor and the same size in bytes as `input` tensor > - `key` tensor can have any dtype and the same device as `input` tensor and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) Also this PR unifies encryption/decryption with existing random number generation which uses AES128 in CTR mode Fixes #77 Differential Revision: [D25080624](https://our.internmc.facebook.com/intern/diff/D25080624) [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 6 ------ torchcsprng/csrc/csprng.h | 8 ++++---- 2 files changed, 4 insertions(+), 10 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index e3822e5..d099b5a 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -131,14 +131,8 @@ void block_cipher( if (output_ptr == nullptr || output_numel == 0) { return; } -// TORCH_CHECK((input_numel * input_type_size + block_size - 1) / block_size * block_size == output_numel * output_type_size, "wrong size"); - -// const auto size_in_bytes = input_numel * input_type_size; -// const auto size_in_bytes = output_numel * output_type_size; if (device.type() == at::kCPU) { -// const auto total = (size_in_bytes + block_size - 1) / block_size; -// const auto total = (size_in_bytes + block_size / N - 1) / block_size * N; const auto total = (output_numel + output_elem_per_block - 1) / output_elem_per_block; block_cipher_kernel_cpu(total, cipher, output_elem_per_block, diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 57c4e54..57d584e 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -67,17 +67,17 @@ at::Tensor key_tensor(size_t block_t_size, c10::optional generato if (gen->key().defined()) { return gen->key().clone(); } - auto t = torch::empty({static_cast(block_t_size)}, torch::kUInt8); - using random_t = uint32_t; + auto key = torch::empty({static_cast(block_t_size)}, torch::kUInt8); + using random_t = typename std::result_of::type; constexpr size_t random_t_size = sizeof(random_t); for (size_t i = 0; i < block_t_size / random_t_size; i++) { const auto rand = gen->random(); for (size_t j = 0; j < random_t_size; j++) { size_t k = i * random_t_size + j; - t[k] = static_cast((rand >> (j * 8)) & 0xff); + key[k] = static_cast((rand >> (j * 8)) & 0xff); } } - return t; + return key; } template From 36545c291cea483c9ce916f520f2cb5eb889d62f Mon Sep 17 00:00:00 2001 From: Pavel Belevich Date: Mon, 30 Nov 2020 11:37:31 -0500 Subject: [PATCH 26/26] Update on "torchcsprng.encrypt/torchcsprng.decrypt with AES128 ECB/CTR support" This PR introduces two new methods to `torchcsprng` module: * `torchcsprng.encrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype and size in bytes(zero-padding is used to make its size in bytes divisible by block size in bytes) > - `output` tensor can have any dtype and the same device as `input` tensor and the size in bytes rounded to the block size in bytes(16 bytes for AES 128) > - `key` tensor can have any dtype and the same device as `input` tensor and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) * `torchcsprng.decrypt(input: Tensor, output: Tensor, key: Tensor, cipher: string, mode: string)` > - `input` tensor can be any CPU or CUDA tensor of any dtype with size in bytes divisible by the block size in bytes(16 bytes for AES 128) > - `output` tensor can have any dtype but the same device as `input` tensor and the same size in bytes as `input` tensor > - `key` tensor can have any dtype and the same device as `input` tensor and size in bytes equal to 16 for AES 128 > - `cipher` currently can be only one supported value `"aes128"` > - `mode` currently can be either [`"ecb"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Electronic_codebook_(ECB)) or [`"ctr"`](https://en.wikipedia.org/wiki/Block_cipher_mode_of_operation#Counter_(CTR)) Also this PR unifies encryption/decryption with existing random number generation which uses AES128 in CTR mode Fixes #77 Differential Revision: [D25080624](https://our.internmc.facebook.com/intern/diff/D25080624) [ghstack-poisoned] --- torchcsprng/csrc/block_cipher.h | 4 ++-- torchcsprng/csrc/csprng.h | 4 +--- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/torchcsprng/csrc/block_cipher.h b/torchcsprng/csrc/block_cipher.h index d099b5a..8418e3d 100644 --- a/torchcsprng/csrc/block_cipher.h +++ b/torchcsprng/csrc/block_cipher.h @@ -37,7 +37,7 @@ TORCH_CSPRNG_HOST_DEVICE static void copy_input_to_block(int64_t idx, uint8_t* b const auto linear_index = idx * (block_size / input_type_size) + i; if (linear_index < input_numel) { std::memcpy( - &(block[i * input_type_size]), + block + i * input_type_size, &(reinterpret_cast(input_ptr)[input_index_calc(linear_index)]), input_type_size ); @@ -53,7 +53,7 @@ TORCH_CSPRNG_HOST_DEVICE static void copy_block_to_output(int64_t idx, uint8_t* if (linear_index < output_numel) { std::memcpy( &(reinterpret_cast(output_ptr)[output_index_calc(linear_index)]), - &(block[i * output_type_size]), + block + i * output_type_size, output_type_size ); } diff --git a/torchcsprng/csrc/csprng.h b/torchcsprng/csrc/csprng.h index 57d584e..cf31c10 100644 --- a/torchcsprng/csrc/csprng.h +++ b/torchcsprng/csrc/csprng.h @@ -516,7 +516,6 @@ void aes_ctr_decrypt(Tensor input, Tensor output, uint8_t* key_bytes) { aes_ctr_encrypt(input, output, key_bytes); } -// Let's assume that input and output have integral dtype, so there is no transform for now. Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { TORCH_CHECK(input.device() == output.device() && input.device() == key.device(), "input, output and key tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); @@ -538,8 +537,7 @@ Tensor encrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string return output; } -// Let's assume that input and output have integral dtype, so there is no transform for now. -Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, std::string cipher, std::string mode) { +Tensor decrypt_pybind(Tensor input, Tensor output, Tensor key, const std::string& cipher, const std::string& mode) { TORCH_CHECK(input.device() == output.device() && input.device() == key.device(), "input, output and key tensors must have the same device"); const auto output_size_bytes = output.numel() * output.itemsize(); const auto input_size_bytes = input.numel() * input.itemsize();