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TFLu: replace old cmsis scratch buffer #37668

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Mar 25, 2020
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TFLu: replace old cmsis scratch buffer #37668

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66 changes: 54 additions & 12 deletions tensorflow/lite/micro/kernels/cmsis-nn/conv.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,6 @@ limitations under the License.
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
#include "tensorflow/lite/kernels/kernel_util.h"
#include "tensorflow/lite/kernels/padding.h"
#include "tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.h"

namespace tflite {
namespace ops {
Expand Down Expand Up @@ -111,12 +110,59 @@ TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteNode* node,
}

void* Init(TfLiteContext* context, const char* buffer, size_t length) {
return nullptr;
void* raw;
context->AllocatePersistentBuffer(
context, sizeof(int), &raw);
return raw;
}

void Free(TfLiteContext* context, void* buffer) {}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
#if defined(__ARM_FEATURE_DSP)
OpData data;
int32_t buf_size;

auto* params = reinterpret_cast<TfLiteConvParams*>(node->builtin_data);

const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
const TfLiteTensor* output = GetOutput(context, node, kOutputTensor);

RuntimeShape input_shape = GetTensorShape(input);

const int input_depth = input_shape.Dims(3);
const int input_width = input->dims->data[2];
const int input_height = input->dims->data[1];
const int filter_width = filter->dims->data[2];
const int filter_height = filter->dims->data[1];
const int output_width = output->dims->data[2];
const int output_height = output->dims->data[1];

int* buffer_idx = reinterpret_cast<int*>(node->user_data);

TF_LITE_ENSURE_STATUS(CalculateOpData(
context, node, params, input_width, input_height, filter_width,
filter_height, output_width, output_height, input->type, &data));

if (data.padding.width == 0 &&
data.padding.height == 0 && (input_depth % 4 == 0) &&
params->stride_width == 1 &&
params->stride_height == 1 && filter_width == 1 && filter_height == 1) {
buf_size = arm_convolve_1x1_s8_fast_get_buffer_size(input_depth);
}
else
{
buf_size = arm_convolve_s8_get_buffer_size(input_depth, filter_width, filter_height);
}

node->user_data = buffer_idx;
if (buf_size > 0) {
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That's a good point. I should check if buf_size is 0.

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I think ideally we should just do

return context->RequestScratchBufferInArena(context, buf_size, buffer_idx)

But let's submit it as it is for now. I'll change the code once I add the check. The only thing that I suggest is to check the return value.

context->RequestScratchBufferInArena(context, buf_size, buffer_idx);
} else {
*buffer_idx = -1;
}
#endif
return kTfLiteOk;
}

Expand Down Expand Up @@ -200,15 +246,16 @@ TfLiteStatus EvalQuantizedPerChannel(
const int output_width = output_shape.Dims(2);
int16_t* buf = nullptr;

auto* buffer_idx = reinterpret_cast<int*>(node->user_data);
if (*buffer_idx > -1) {
void *raw = context->GetScratchBuffer(context, *buffer_idx);
buf = reinterpret_cast<int16_t*>(raw);
}

if (op_params.padding_values.width == 0 &&
op_params.padding_values.height == 0 && (input_depth % 4 == 0) &&
(output_depth % 2 == 0) && op_params.stride_width == 1 &&
op_params.stride_height == 1 && filter_width == 1 && filter_height == 1) {
const int32_t buf_size =
arm_convolve_1x1_s8_fast_get_buffer_size(input_depth);
if (get_cmsis_scratch_buffer(context, &buf, buf_size) != kTfLiteOk) {
return kTfLiteError;
}
if (arm_convolve_1x1_s8_fast(
GetTensorData<int8_t>(input), input_width, input_height,
input_depth, batches, GetTensorData<int8_t>(filter), output_depth,
Expand All @@ -222,11 +269,6 @@ TfLiteStatus EvalQuantizedPerChannel(
return kTfLiteError;
}
} else {
const int32_t buf_size = arm_convolve_s8_get_buffer_size(
input_depth, filter_width, filter_height);
if (get_cmsis_scratch_buffer(context, &buf, buf_size) != kTfLiteOk) {
return kTfLiteError;
}
if (arm_convolve_s8(
GetTensorData<int8_t>(input), input_width, input_height,
input_depth, batches, GetTensorData<int8_t>(filter), output_depth,
Expand Down
41 changes: 35 additions & 6 deletions tensorflow/lite/micro/kernels/cmsis-nn/depthwise_conv.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,6 @@ limitations under the License.
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
#include "tensorflow/lite/kernels/kernel_util.h"
#include "tensorflow/lite/kernels/padding.h"
#include "tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.h"

namespace tflite {
namespace ops {
Expand Down Expand Up @@ -99,12 +98,40 @@ TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteNode* node,
} // namespace

void* Init(TfLiteContext* context, const char* buffer, size_t length) {
return nullptr;
void* raw;
context->AllocatePersistentBuffer(
context, sizeof(int), &raw);
return raw;
}

void Free(TfLiteContext* context, void* buffer) {}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
#if defined(__ARM_FEATURE_DSP)
auto* params = reinterpret_cast<TfLiteDepthwiseConvParams*>(node->builtin_data);

const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);

const int filter_width = SizeOfDimension(filter, 2);
const int filter_height = SizeOfDimension(filter, 1);

RuntimeShape input_shape = GetTensorShape(input);
const int input_depth = input_shape.Dims(3);

int* buffer_idx = reinterpret_cast<int*>(node->user_data);

*buffer_idx = -1;
node->user_data = buffer_idx;

if (params->depth_multiplier == 1) {
const int32_t buf_size = arm_depthwise_conv_s8_opt_get_buffer_size(input_depth, filter_width, filter_height);

if (buf_size > 0) {
context->RequestScratchBufferInArena(context, buf_size, buffer_idx);
}
}
#endif
return kTfLiteOk;
}

Expand Down Expand Up @@ -174,10 +201,12 @@ TfLiteStatus EvalQuantizedPerChannel(TfLiteContext* context, TfLiteNode* node,

if (op_params.depth_multiplier == 1) {
int16_t* buf = nullptr;
const int32_t buf_size = arm_depthwise_conv_s8_opt_get_buffer_size(
input_depth, filter_width, filter_height);
TF_LITE_ENSURE_OK(context,
get_cmsis_scratch_buffer(context, &buf, buf_size));
auto* buffer_idx = reinterpret_cast<int*>(node->user_data);
if (*buffer_idx > -1) {
void *raw = context->GetScratchBuffer(context, *buffer_idx);
buf = reinterpret_cast<int16_t*>(raw);
}

TF_LITE_ENSURE_EQ(
context,
arm_depthwise_conv_s8_opt(
Expand Down
35 changes: 29 additions & 6 deletions tensorflow/lite/micro/kernels/cmsis-nn/fully_connected.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,6 @@ limitations under the License.
#include "tensorflow/lite/kernels/internal/reference/integer_ops/fully_connected.h"
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
#include "tensorflow/lite/kernels/kernel_util.h"
#include "tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.h"

namespace tflite {
namespace ops {
Expand Down Expand Up @@ -73,14 +72,33 @@ TfLiteStatus CalculateOpData(TfLiteContext* context,
} // namespace

void* Init(TfLiteContext* context, const char* buffer, size_t length) {
return nullptr;
void* raw;
context->AllocatePersistentBuffer(
context, sizeof(int), &raw);
return raw;
}

void Free(TfLiteContext* context, void* buffer) {}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
// todo: call AllocateTemporaryTensor() instead of using
// get_cmsis_scratch_buffer()
#if defined(__ARM_FEATURE_DSP)
const TfLiteTensor* filter = GetInput(context, node, kWeightsTensor);

RuntimeShape filter_shape = GetTensorShape(filter);
const int filter_dim_count = filter_shape.DimensionsCount();
const int accum_depth = filter_shape.Dims(filter_dim_count - 1);

const int32_t buf_size = arm_fully_connected_s8_get_buffer_size(accum_depth);

int* buffer_idx = reinterpret_cast<int*>(node->user_data);

node->user_data = buffer_idx;
if (buf_size > 0) {
context->RequestScratchBufferInArena(context, buf_size, buffer_idx);
} else {
*buffer_idx = -1;
}
#endif
return kTfLiteOk;
}

Expand All @@ -97,9 +115,14 @@ TfLiteStatus EvalQuantizedInt8(TfLiteContext* context, TfLiteNode* node,
const int accum_depth = filter_shape.Dims(filter_dim_count - 1);

#if defined(__ARM_FEATURE_DSP)
const int32_t buf_size = arm_fully_connected_s8_get_buffer_size(accum_depth);
int16_t* buf = nullptr;
TF_LITE_ENSURE_OK(context, get_cmsis_scratch_buffer(context, &buf, buf_size));

auto* buffer_idx = reinterpret_cast<int*>(node->user_data);
if (*buffer_idx > -1) {
void *raw = context->GetScratchBuffer(context, *buffer_idx);
buf = reinterpret_cast<int16_t*>(raw);
}

TF_LITE_ENSURE_EQ(
context,
arm_fully_connected_s8(
Expand Down
39 changes: 34 additions & 5 deletions tensorflow/lite/micro/kernels/cmsis-nn/pooling.cc
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Expand Up @@ -16,7 +16,6 @@ limitations under the License.

// These are headers from the ARM CMSIS-NN library.
#include "arm_nnfunctions.h" // NOLINT
#include "scratch_buffer.h" // NOLINT
#include "tensorflow/lite/c/builtin_op_data.h"
#include "tensorflow/lite/kernels/internal/reference/integer_ops/pooling.h"
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
Expand Down Expand Up @@ -128,10 +127,13 @@ TfLiteStatus AverageEvalInt8(TfLiteContext* context, const TfLiteNode* node,
const int padding_width = data->padding.width;

int16_t* scratch_buffer = nullptr;
int32_t buffer_size = arm_avgpool_s8_get_buffer_size(output_width, depth);

TF_LITE_ENSURE_OK(
context, get_cmsis_scratch_buffer(context, &scratch_buffer, buffer_size));
auto* buffer_idx = reinterpret_cast<int*>(node->user_data);

if (*buffer_idx > -1) {
void *raw = context->GetScratchBuffer(context, *buffer_idx);
scratch_buffer = reinterpret_cast<int16_t*>(raw);
}

TF_LITE_ENSURE_EQ(
context,
Expand Down Expand Up @@ -207,12 +209,39 @@ void MaxEvalQuantizedUInt8(TfLiteContext* context, TfLiteNode* node,
} // namespace

void* Init(TfLiteContext* context, const char* buffer, size_t length) {
return nullptr;
void* raw;
context->AllocatePersistentBuffer(
context, sizeof(int), &raw);
return raw;
}

void Free(TfLiteContext* context, void* buffer) {}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
#if defined(__ARM_FEATURE_DSP)
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* output = GetOutput(context, node, kOutputTensor);

RuntimeShape input_shape = GetTensorShape(input);
TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);

RuntimeShape output_shape = GetTensorShape(output);
TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);

const int depth = MatchingDim(input_shape, 3, output_shape, 3);
const int output_width = output_shape.Dims(2);

const int32_t buffer_size = arm_avgpool_s8_get_buffer_size(output_width, depth);

int* buffer_idx = reinterpret_cast<int*>(node->user_data);

node->user_data = buffer_idx;
if (buffer_size > 0) {
context->RequestScratchBufferInArena(context, buffer_size, buffer_idx);
} else {
*buffer_idx = -1;
}
#endif
return kTfLiteOk;
}

Expand Down
36 changes: 0 additions & 36 deletions tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.cc
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This file was deleted.

26 changes: 0 additions & 26 deletions tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.h
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This file was deleted.

7 changes: 0 additions & 7 deletions tensorflow/lite/micro/tools/make/ext_libs/cmsis.inc
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Expand Up @@ -21,13 +21,6 @@ ifneq ($(filter cmsis-nn,$(ALL_TAGS)),)
THIRD_PARTY_CC_HDRS += \
$(call recursive_find,$(CMSIS_PATH)/CMSIS/Core/Include,*.h)

# todo: remove the two lines below once context->AllocateTemporaryTensor()
# is implemented.
MICROLITE_CC_HDRS += \
tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.h
MICROLITE_CC_SRCS += \
tensorflow/lite/micro/kernels/cmsis-nn/scratch_buffer.cc

INCLUDES += -I$(CMSIS_PATH)/CMSIS/Core/Include \
-I$(CMSIS_PATH)/CMSIS/NN/Include \
-I$(CMSIS_PATH)/CMSIS/DSP/Include
Expand Down
2 changes: 2 additions & 0 deletions tensorflow/lite/micro/tools/make/targets/stm32f4_makefile.inc
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Expand Up @@ -76,6 +76,8 @@ ifeq ($(TARGET), stm32f4)
tensorflow/lite/micro/kernels/dequantize_test.cc \
tensorflow/lite/micro/kernels/unpack_test.cc \
tensorflow/lite/micro/kernels/split_test.cc \
tensorflow/lite/micro/kernels/conv_test.cc \
tensorflow/lite/micro/kernels/depthwise_conv_test.cc \
tensorflow/lite/micro/simple_tensor_allocator_test.cc
MICROLITE_TEST_SRCS := $(filter-out $(EXCLUDED_TESTS), $(MICROLITE_TEST_SRCS))
EXCLUDED_EXAMPLE_TESTS := \
Expand Down