experiments/STT-tensorflow
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Automatic readability finding fixes.

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PiperOrigin-RevId: 324682656
Change-Id: I009a949fbf08eeb5e45d19d8a1918a988960311b
This commit is contained in:
Robert David 2020-08-03 14:22:57 -07:00 committed by TensorFlower Gardener
parent b58a8717b1
commit 6dbc50195e
5 changed files with 15 additions and 20 deletions
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3
tensorflow/lite/delegates/gpu/gl/object_manager.cc
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@ -40,8 +40,7 @@ absl::Status CreatePHWC4BufferFromTensorRef(const TensorRef<BHWC>& tensor_ref,
absl::Status CopyFromPHWC4Buffer(const GlBuffer& buffer,
TensorFloat32* tensor) {
return buffer.MappedRead<float>(
[tensor, &buffer](absl::Span<const float> data) {
return buffer.MappedRead<float>([tensor](absl::Span<const float> data) {
tensor->data.resize(tensor->shape.DimensionsProduct());
return ConvertFromPHWC4(absl::MakeConstSpan(data), tensor->shape,
absl::MakeSpan(tensor->data));

2
tensorflow/lite/delegates/gpu/metal/kernels/elementwise.cc
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@ -115,7 +115,7 @@ std::vector<ComputeTaskDescriptorPtr> ElementwiseWithTwoInputs(
desc->uniform_buffers = {
{"constant int2&",
[input_ids, output_id](const std::map<ValueId, BHWC>& buffers) {
[input_ids](const std::map<ValueId, BHWC>& buffers) {
const auto& input_dim_1 = buffers.find(input_ids[1])->second;
std::vector<int> uniform_params{
input_dim_1.w,

14
tensorflow/lite/delegates/gpu/metal/kernels/max_unpooling.cc
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@ -99,17 +99,15 @@ std::vector<ComputeTaskDescriptorPtr> MaxUnpooling(
{input_indices_id, "device FLT4* const src_indices_buffer"},
};
desc->output_buffer = {output_id, "device FLT4* output_buffer",
[input_id, input_indices_id,
params](const std::map<ValueId, BHWC>& buffers) {
return CalculateOutputShape(
buffers.find(input_id)->second, params);
desc->output_buffer = {
output_id, "device FLT4* output_buffer",
[input_id, params](const std::map<ValueId, BHWC>& buffers) {
return CalculateOutputShape(buffers.find(input_id)->second, params);
}};
desc->uniform_buffers = {
{"constant uniforms& params",
[input_id, input_indices_id, output_id,
params](const std::map<ValueId, BHWC>& buffers) {
[input_id, output_id, params](const std::map<ValueId, BHWC>& buffers) {
const auto& dimension = buffers.find(input_id)->second;
const auto& output_dimension = buffers.find(output_id)->second;
std::vector<int> uniform_params{
@ -126,7 +124,7 @@ std::vector<ComputeTaskDescriptorPtr> MaxUnpooling(
}},
};
desc->resize_function = [input_id, input_indices_id,
desc->resize_function = [input_id,
params](const std::map<ValueId, BHWC>& buffers) {
const auto& src_shape = buffers.find(input_id)->second;
BHWC dst_shape = CalculateOutputShape(src_shape, params);

3
tensorflow/lite/delegates/gpu/metal/kernels/mean.cc
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@ -130,8 +130,7 @@ std::vector<ComputeTaskDescriptorPtr> Mean(int id, ValueId input_id,
}};
desc->uniform_buffers = {
{"constant uniforms& params",
[input_id, output_id,
work_group_size](const std::map<ValueId, BHWC>& buffers) {
[input_id, work_group_size](const std::map<ValueId, BHWC>& buffers) {
const auto& src_shape = buffers.find(input_id)->second;
const int src_slices = DivideRoundUp(src_shape.c, 4);
struct uniforms {

3
tensorflow/lite/delegates/gpu/metal/kernels/winograd.cc
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@ -613,8 +613,7 @@ std::vector<ComputeTaskDescriptorPtr> Winograd4x4To36TileX6(
}},
};
desc->resize_function = [output_id,
attr](const std::map<ValueId, BHWC>& buffers) {
desc->resize_function = [output_id](const std::map<ValueId, BHWC>& buffers) {
const uint3 groups_size{4, 6, 1};
const auto& dst_shape = buffers.find(output_id)->second;
int grid_x = dst_shape.w;