experiments/STT-tensorflow
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Be more pedantic about type conversions to avoid warning on Windows.

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PiperOrigin-RevId: 297716959
Change-Id: I5bc28c70a988448e90e8acf3ab877ac017879b0a
This commit is contained in:
Artem Belevich 2020-02-27 16:25:37 -08:00 committed by TensorFlower Gardener
parent 688b902589
commit 24fe4c1a0d
7 changed files with 22 additions and 14 deletions
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7
tensorflow/lite/toco/graph_transformations/propagate_fixed_sizes.cc
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@ -1885,9 +1885,12 @@ void ProcessSparseToDenseOperator(Model* model, SparseToDenseOperator* op) {
} else {
const std::vector<int64>& output_shape_data =
output_shape_array.GetBuffer<ArrayDataType::kInt64>().data;
std::copy(
// explicitly cast elements to int in order to avoid MSVC warnings about
// narrowing conversion.
std::transform(
output_shape_data.begin(), output_shape_data.end(),
std::back_inserter(*output_array.mutable_shape()->mutable_dims()));
std::back_inserter(*output_array.mutable_shape()->mutable_dims()),
[](const int64 dim) { return static_cast<int>(dim); });
}
}

5
tensorflow/lite/toco/graph_transformations/resolve_constant_tile.cc
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@ -64,8 +64,9 @@ std::pair<int, int> TileOneDimension(const Shape& in_dimensions,
CopyMultipleTimes(out_data, total_tiled_stride_size,
multipliers[dimension] - 1,
out_data + total_tiled_stride_size);
return std::make_pair(total_stride_size,
total_tiled_stride_size * multipliers[dimension]);
return std::make_pair(
total_stride_size,
static_cast<int>(total_tiled_stride_size * multipliers[dimension]));
}
template <ArrayDataType Type>

7
tensorflow/lite/toco/graph_transformations/unroll_batch_matmul.cc
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@ -241,8 +241,11 @@ TransposeOperator* TransposeInput(const string& input, Model* model) {
// Reshape the rank-3 Tensor into the correct output shape.
const auto& result_batch_shape = bcast.output_batch_shape().dim_sizes();
std::vector<int> result_shape(result_batch_shape.begin(),
result_batch_shape.end());
std::vector<int> result_shape;
// Explicitly cast 64-bit sizes to int in order to avoid MSVC warnings.
std::transform(result_batch_shape.begin(), result_batch_shape.end(),
std::back_inserter(result_shape),
[](const int64 dim) { return static_cast<int>(dim); });
result_shape.push_back(input_array_a.shape().dims(dims_a - 2));
result_shape.push_back(input_array_b.shape().dims(dims_b - 1));

3
tensorflow/lite/toco/import_tensorflow.cc
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@ -533,7 +533,8 @@ string CreateConstArray(Model* model, string const& name,
string array_name = toco::AvailableArrayName(*model, name);
auto& array = model->GetOrCreateArray(array_name);
array.data_type = T;
array.mutable_shape()->mutable_dims()->emplace_back(data.size());
array.mutable_shape()->mutable_dims()->emplace_back(
static_cast<int>(data.size()));
array.GetMutableBuffer<T>().data = data;
return array_name;
}

10
tensorflow/lite/tools/optimize/operator_property.cc
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@ -176,7 +176,7 @@ OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
// LogSoftmax requires output with 16/256 as scale and 127 as zero point.
TensorProperty tensor_property;
tensor_property.restriction = true;
tensor_property.restricted_value = {16.0 / 256.0, 127};
tensor_property.restricted_value = {16.0f / 256.0f, 127};
property.outputs = {{0, tensor_property}};
property.version = 2;
break;
@ -186,7 +186,7 @@ OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
// Logistic requires output with 1/256 as scale and -128 as zero point.
TensorProperty tensor_property;
tensor_property.restriction = true;
tensor_property.restricted_value = {1 / 256.0, -128};
tensor_property.restricted_value = {1 / 256.0f, -128};
property.outputs = {{0, tensor_property}};
property.version = 2;
break;
@ -741,7 +741,7 @@ OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
// L2 Norm requires output with 1/128 as scale and 0 as zero point.
TensorProperty tensor_property;
tensor_property.restriction = true;
tensor_property.restricted_value = {1 / 128.0, 0};
tensor_property.restricted_value = {1 / 128.0f, 0};
property.outputs = {{0, tensor_property}};
property.version = 2;
break;
@ -841,7 +841,7 @@ OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
// Softmax requires output with 1/256 as scale and -128 as zero point.
TensorProperty tensor_property;
tensor_property.restriction = true;
tensor_property.restricted_value = {1 / 256.0, -128};
tensor_property.restricted_value = {1 / 256.0f, -128};
property.outputs = {{0, tensor_property}};
property.version = 2;
break;
@ -867,7 +867,7 @@ OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
// Tanh requires output with 1/128 as scale and 0 as zero point.
TensorProperty tensor_property;
tensor_property.restriction = true;
tensor_property.restricted_value = {1 / 128.0, 0};
tensor_property.restricted_value = {1 / 128.0f, 0};
property.outputs = {{0, tensor_property}};
property.version = 2;
break;

2
tensorflow/lite/tools/optimize/operator_property.h
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@ -43,7 +43,7 @@ struct TensorProperty {
// Constraints.
bool restriction = false;
// scale/zero_point hardcoded.
std::pair<float, int> restricted_value = {0.0, 0};
std::pair<float, int> restricted_value = {0.0f, 0};
// Use derived scale.
bool use_derived_scale = false;

2
tensorflow/lite/tools/optimize/sparsity/format_converter.cc
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@ -304,7 +304,7 @@ void FormatConverter<T>::Populate(const T* src_data, std::vector<int> indices,
template <typename T>
TfLiteStatus FormatConverter<T>::SparseToDense(const T* src_data) {
data_.resize(dense_size_);
std::fill(data_.begin(), data_.end(), 0);
std::fill(data_.begin(), data_.end(), T(0));
int total_rank = traversal_order_.size();
int src_data_ptr = 0;