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Merged
dlibenzi merged 1 commit into from
May 30, 2019
Merged

Re-align code after PT Variable code changes. #713

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1 change: 0 additions & 1 deletion .torch_commit_id
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174 changes: 21 additions & 153 deletions test/cpp/test_aten_xla_tensor.cpp
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
#include <ATen/ATen.h>
#include <ATen/LegacyTHFunctions.h>
#include <ATen/NativeFunctions.h>
#include <gtest/gtest.h>
#include <torch/csrc/autograd/function.h>
Expand Down Expand Up @@ -381,18 +380,6 @@ TEST_F(AtenXlaTensorTest, TestNeInplace) {
});
}

TEST_F(AtenXlaTensorTest, TestThNe) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor c = at::_th_ne(a, b);
ForEachDevice([&](const Device& device) {
at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
at::Tensor xla_b = bridge::CreateXlaTensor(b, device);
at::Tensor xla_c = at::_th_ne(xla_a, xla_b);
AllClose(c, xla_c);
});
}

TEST_F(AtenXlaTensorTest, TestEq) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = a.clone();
Expand All @@ -419,43 +406,6 @@ TEST_F(AtenXlaTensorTest, TestEqInplace) {
});
}

TEST_F(AtenXlaTensorTest, TestThEq) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = a.clone();
at::Tensor c = at::_th_eq(a, b);
ForEachDevice([&](const Device& device) {
at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
at::Tensor xla_b = bridge::CreateXlaTensor(b, device);
at::Tensor xla_c = at::_th_eq(xla_a, xla_b);
AllClose(c, xla_c);
});
}

TEST_F(AtenXlaTensorTest, TestThEqScalar) {
at::Tensor a = at::full({}, 1.2, at::TensorOptions(at::kFloat));
at::Tensor b = at::_th_eq(a, 1.2);
ForEachDevice([&](const Device& device) {
at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
at::Tensor xla_b = at::_th_eq(xla_a, 1.2);
AllClose(b, xla_b);
});
}

TEST_F(AtenXlaTensorTest, TestThEqAutograd) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = a.clone();
at::Tensor c = at::_th_eq(torch::autograd::make_variable(a, false),
torch::autograd::make_variable(b, false));
ForEachDevice([&](const Device& device) {
at::Tensor xla_a = torch::autograd::make_variable(
bridge::CreateXlaTensor(a, device), false);
at::Tensor xla_b = torch::autograd::make_variable(
bridge::CreateXlaTensor(b, device), false);
at::Tensor xla_c = at::_th_eq(xla_a, xla_b);
EXPECT_TRUE(EqualValues(c, xla_c));
});
}

TEST_F(AtenXlaTensorTest, TestGe) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = a.clone();
Expand Down Expand Up @@ -510,18 +460,6 @@ TEST_F(AtenXlaTensorTest, TestLeInplace) {
});
}

TEST_F(AtenXlaTensorTest, TestThLe) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = a.clone();
at::Tensor c = at::_th_le(a, b);
ForEachDevice([&](const Device& device) {
at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
at::Tensor xla_b = bridge::CreateXlaTensor(b, device);
at::Tensor xla_c = at::_th_le(xla_a, xla_b);
AllClose(c, xla_c);
});
}

TEST_F(AtenXlaTensorTest, TestGt) {
at::Tensor a = at::rand({2, 3}, at::TensorOptions(at::kFloat));
at::Tensor b = at::add(a.clone(), at::ones_like(a));
Expand Down Expand Up @@ -587,17 +525,6 @@ TEST_F(AtenXlaTensorTest, TestNeScalar) {
});
}

TEST_F(AtenXlaTensorTest, TestThNeScalar) {
at::Tensor input = at::ones({2, 3});
at::Scalar other(float(0));
at::Tensor result = at::_th_ne(input, other);
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input, device);
at::Tensor xla_result = at::_th_ne(xla_input, other);
AllClose(result, xla_result);
});
}

TEST_F(AtenXlaTensorTest, TestEqScalar) {
at::Tensor input = at::ones({2, 3});
at::Scalar other(float(1));
Expand Down Expand Up @@ -655,17 +582,6 @@ TEST_F(AtenXlaTensorTest, TestLeScalarInplace) {
});
}

TEST_F(AtenXlaTensorTest, TestThLeScalar) {
at::Tensor input = at::ones({2, 3});
at::Scalar other(float(1));
at::Tensor result = at::_th_le(input, other);
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input, device);
at::Tensor xla_result = at::_th_le(xla_input, other);
AllClose(result, xla_result);
});
}

TEST_F(AtenXlaTensorTest, TestGtScalar) {
at::Tensor input = at::ones({2, 3});
at::Scalar other(float(0.5));
Expand Down Expand Up @@ -4459,21 +4375,21 @@ TEST_F(AtenXlaTensorTest, TestMaxPool3DIncompleteAttributes) {
for (bool ceil_mode : {false, true}) {
// Test dilation through the CPU interop.
for (int dilation = 1; dilation <= 2; ++dilation) {
at::Tensor output =
at::max_pool3d(input, /*kernel_size=*/{kernel_size},
/*stride=*/{},
/*padding=*/{padding},
/*dilation=*/{dilation, dilation, dilation},
/*ceil_mode=*/ceil_mode);
at::Tensor output = at::max_pool3d(
input, /*kernel_size=*/{kernel_size, kernel_size, kernel_size},
/*stride=*/{},
/*padding=*/{padding},
/*dilation=*/{dilation, dilation, dilation},
/*ceil_mode=*/ceil_mode);
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input, device);
at::Tensor xla_output =
at::max_pool3d(xla_input,
/*kernel_size=*/{kernel_size},
/*stride=*/{},
/*padding=*/{padding},
/*dilation=*/{dilation, dilation, dilation},
/*ceil_mode=*/ceil_mode);
at::Tensor xla_output = at::max_pool3d(
xla_input,
/*kernel_size=*/{kernel_size, kernel_size, kernel_size},
/*stride=*/{},
/*padding=*/{padding},
/*dilation=*/{dilation, dilation, dilation},
/*ceil_mode=*/ceil_mode);
AllClose(output, xla_output);
});
}
Expand Down Expand Up @@ -5928,56 +5844,8 @@ TEST_F(AtenXlaTensorTest, TestBitwiseXorScalarInPlace) {
});
}

TEST_F(AtenXlaTensorTest, TestBitwiseAndAutograd) {
at::Tensor lhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor rhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor result = at::legacy::th::__and__(lhs, rhs);
ForEachDevice([&](const Device& device) {
at::Tensor xla_lhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(lhs, device), false);
at::Tensor xla_rhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(rhs, device), false);
at::Tensor xla_result = at::legacy::th::__and__(xla_lhs, xla_rhs);
AllClose(result, xla_result);
});
}

TEST_F(AtenXlaTensorTest, TestBitwiseOrAutograd) {
at::Tensor lhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor rhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor result = at::legacy::th::__or__(lhs, rhs);
ForEachDevice([&](const Device& device) {
at::Tensor xla_lhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(lhs, device), false);
at::Tensor xla_rhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(rhs, device), false);
at::Tensor xla_result = at::legacy::th::__or__(xla_lhs, xla_rhs);
AllClose(result, xla_result);
});
}

TEST_F(AtenXlaTensorTest, TestBitwiseXorAutograd) {
at::Tensor lhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor rhs = at::randint(0, std::numeric_limits<int32_t>::max(), {4, 2},
at::TensorOptions(at::kInt));
at::Tensor result = at::legacy::th::__xor__(lhs, rhs);
ForEachDevice([&](const Device& device) {
at::Tensor xla_lhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(lhs, device), false);
at::Tensor xla_rhs = torch::autograd::make_variable(
bridge::CreateXlaTensor(rhs, device), false);
at::Tensor xla_result = at::legacy::th::__xor__(xla_lhs, xla_rhs);
AllClose(result, xla_result);
});
}

TEST_F(AtenXlaTensorTest, TestLshift) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor shift_amount = at::randint(16, input.sizes());
at::Tensor result = at::__lshift__(input, shift_amount);
ForEachDevice([&](const Device& device) {
Expand All @@ -5989,7 +5857,7 @@ TEST_F(AtenXlaTensorTest, TestLshift) {
}

TEST_F(AtenXlaTensorTest, TestLshiftInPlace) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input.clone(), device);
at::Tensor shift_amount = at::randint(16, input.sizes());
Expand All @@ -6002,7 +5870,7 @@ TEST_F(AtenXlaTensorTest, TestLshiftInPlace) {
}

TEST_F(AtenXlaTensorTest, TestLshiftScalar) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Scalar shift_amount = 3;
at::Tensor result = at::__lshift__(input, shift_amount);
ForEachDevice([&](const Device& device) {
Expand All @@ -6013,7 +5881,7 @@ TEST_F(AtenXlaTensorTest, TestLshiftScalar) {
}

TEST_F(AtenXlaTensorTest, TestLshiftScalarInPlace) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Scalar shift_amount = 3;
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input.clone(), device);
Expand All @@ -6025,7 +5893,7 @@ TEST_F(AtenXlaTensorTest, TestLshiftScalarInPlace) {
}

TEST_F(AtenXlaTensorTest, TestRshift) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor shift_amount = at::randint(16, input.sizes());
at::Tensor result = at::__rshift__(input, shift_amount);
ForEachDevice([&](const Device& device) {
Expand All @@ -6037,7 +5905,7 @@ TEST_F(AtenXlaTensorTest, TestRshift) {
}

TEST_F(AtenXlaTensorTest, TestRshiftInPlace) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input.clone(), device);
at::Tensor shift_amount = at::randint(16, input.sizes());
Expand All @@ -6050,7 +5918,7 @@ TEST_F(AtenXlaTensorTest, TestRshiftInPlace) {
}

TEST_F(AtenXlaTensorTest, TestRshiftScalar) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Scalar shift_amount = 3;
at::Tensor result = at::__rshift__(input, shift_amount);
ForEachDevice([&](const Device& device) {
Expand All @@ -6061,7 +5929,7 @@ TEST_F(AtenXlaTensorTest, TestRshiftScalar) {
}

TEST_F(AtenXlaTensorTest, TestRshiftScalarInPlace) {
at::Tensor input = at::randn({4, 2}, at::TensorOptions(at::kFloat));
at::Tensor input = at::ones({4, 2}, at::TensorOptions(at::kFloat));
at::Scalar shift_amount = 3;
ForEachDevice([&](const Device& device) {
at::Tensor xla_input = bridge::CreateXlaTensor(input.clone(), device);
Expand Down
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