/aosp_15_r20/external/tensorflow/tensorflow/compiler/xla/tests/ |
H A D | convolution_variants_test.cc | 56 const Array4D<float> input_array(1, 1, 1, 1, {2}); in XLA_TEST_F() local 57 auto input = ConstantR4FromArray4D<float>(&builder, input_array); in XLA_TEST_F() 71 const Array4D<float> input_array(5, 1, 1, 1, {1, 2, 3, 4, 5}); in XLA_TEST_F() local 72 auto input = ConstantR4FromArray4D<float>(&builder, input_array); in XLA_TEST_F() 86 Array4D<float> input_array(2, 1, 3, 4); in XLA_TEST_F() local 87 input_array.FillWithMultiples(1); in XLA_TEST_F() 88 auto input = ConstantR4FromArray4D<float>(&builder, input_array); in XLA_TEST_F() 103 Array4D<float> input_array(1, 2, 1, 1, {10, 1}); in XLA_TEST_F() local 104 auto input = ConstantR4FromArray4D<float>(&builder, input_array); in XLA_TEST_F() 118 Array4D<float> input_array(1, 1, 1, 2, {1, 2}); in XLA_TEST_F() local [all …]
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H A D | reduce_window_test.cc | 163 Array4D<float> input_array(1, 0, 2, 1); in XLA_TEST_P() local 164 const auto input = CreateConstantFromArray(input_array, &builder_); in XLA_TEST_P() 168 auto res = ReferenceUtil::ReduceWindow4DAdd(input_array, 0.0f, {1, 1, 2, 1}, in XLA_TEST_P() 176 Array4D<float> input_array(1, 2, 2, 1); in XLA_TEST_P() local 177 input_array.FillRandom(2.f, 2.f); in XLA_TEST_P() 178 const auto input = CreateConstantFromArray(input_array, &builder_); in XLA_TEST_P() 183 auto res = ReferenceUtil::ReduceWindow4DAdd(input_array, 0.0f, {1, 1, 2, 1}, in XLA_TEST_P() 191 Array4D<float> input_array(1, 3, 3, 1); in XLA_TEST_P() local 192 input_array.FillRandom(2.f, 2.f); in XLA_TEST_P() 193 const auto input = CreateConstantFromArray(input_array, &builder_); in XLA_TEST_P() [all …]
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H A D | batch_normalization_test.cc | 516 Array4D<float> input_array(bounds[0], bounds[1], bounds[2], bounds[3]); in XLA_TEST_P() local 517 input_array.FillRandom(GetParam().random_value_var, in XLA_TEST_P() 528 ReferenceUtil::MapArray4D(input_array, [](float a) { return a * a; }); in XLA_TEST_P() 537 ReferenceUtil::Reduce4DTo1D(input_array, /*init=*/0.0f, reduce_dims, in XLA_TEST_P() 572 auto normalized = *ReferenceUtil::BatchNorm4D(input_array, mean4D, var4D, in XLA_TEST_P() 580 auto input_literal = LiteralUtil::CreateR4FromArray4D<float>(input_array); in XLA_TEST_P() 617 Array4D<float> input_array(bounds[0], bounds[1], bounds[2], bounds[3]); in XLA_TEST_P() local 618 input_array.FillRandom(GetParam().random_value_var, in XLA_TEST_P() 629 ReferenceUtil::MapArray4D(input_array, [](float a) { return a * a; }); in XLA_TEST_P() 638 ReferenceUtil::Reduce4DTo1D(input_array, /*init=*/0.0f, reduce_dims, in XLA_TEST_P() [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
H A D | propagate_fixed_sizes.cc | 126 const auto& input_array = model->GetArray(op->inputs[0]); in ProcessConvOperator() local 128 if (!input_array.has_shape()) { in ProcessConvOperator() 131 const auto& input_shape = input_array.shape(); in ProcessConvOperator() 222 const auto& input_array = in ProcessTransposeConvOperator() local 224 if (!input_array.has_shape()) { in ProcessTransposeConvOperator() 228 const auto& input_shape = input_array.shape(); in ProcessTransposeConvOperator() 253 const auto& input_array = model->GetArray(op->inputs[0]); in ProcessDepthwiseConvOperator() local 255 if (!input_array.has_shape()) { in ProcessDepthwiseConvOperator() 258 const auto& input_shape = input_array.shape(); in ProcessDepthwiseConvOperator() 295 const auto& input_array = model->GetArray(op->inputs[0]); in ProcessDepthToSpaceOperator() local [all …]
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H A D | resolve_constant_reshape.cc | 55 const Array& input_array = model->GetArray(op->inputs[0]); in Run() local 56 if (!ShapesAgreeUpToExtending(input_array.shape(), output_array.shape())) { in Run() 58 ShapeToString(input_array.shape()), in Run() 64 switch (input_array.data_type) { in Run() 66 CopyArrayBuffer<ArrayDataType::kBool>(input_array, &output_array); in Run() 69 CopyArrayBuffer<ArrayDataType::kFloat>(input_array, &output_array); in Run() 72 CopyArrayBuffer<ArrayDataType::kInt8>(input_array, &output_array); in Run() 75 CopyArrayBuffer<ArrayDataType::kUint8>(input_array, &output_array); in Run() 78 CopyArrayBuffer<ArrayDataType::kInt16>(input_array, &output_array); in Run() 81 CopyArrayBuffer<ArrayDataType::kUint16>(input_array, &output_array); in Run() [all …]
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H A D | make_initial_dequantize_operator.cc | 56 auto& input_array = model->GetArray(input_name); in AddDequantizeOperatorToInput() local 57 if (input_array.data_type != ArrayDataType::kFloat) { in AddDequantizeOperatorToInput() 61 if (input_array.final_data_type == input_array.data_type || in AddDequantizeOperatorToInput() 62 input_array.final_data_type == ArrayDataType::kNone) { in AddDequantizeOperatorToInput() 84 const auto& input_minmax = input_array.GetMinMax(); in AddDequantizeOperatorToInput() 87 auto& input_qparams = input_array.GetOrCreateQuantizationParams(); in AddDequantizeOperatorToInput() 88 input_array.data_type = input_array.final_data_type; in AddDequantizeOperatorToInput() 90 input_array, input_array.data_type, &input_qparams); in AddDequantizeOperatorToInput() 111 for (auto& input_array : *model->flags.mutable_input_arrays()) { in Run() 112 if (input_array.name() == input) { in Run() [all …]
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H A D | resolve_reorder_axes.cc | 59 const Array& input_array, Array* output_array) { in ReorderAxes() argument 60 DCHECK(input_array.buffer->type == DataType); in ReorderAxes() 62 const auto& input_data = input_array.GetBuffer<DataType>().data; in ReorderAxes() 66 Shape input_shape = input_array.shape(); in ReorderAxes() 74 if (input_array.minmax) { in ReorderAxes() 75 output_array->GetOrCreateMinMax() = input_array.GetMinMax(); in ReorderAxes() 77 if (input_array.narrow_range) { in ReorderAxes() 96 auto& input_array = model->GetArray(input_array_name); in Run() local 98 if (!input_array.buffer) { in Run() 106 if (input_array.buffer->type == ArrayDataType::kFloat) { in Run() [all …]
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H A D | resolve_constant_unary.cc | 105 const auto& input_array = model->GetArray(op.inputs[0]); in CopyMinMaxFromFirstInput() local 106 if (!input_array.minmax) { in CopyMinMaxFromFirstInput() 109 const auto& input_minmax = input_array.GetMinMax(); in CopyMinMaxFromFirstInput() 183 const auto& input_array = model->GetArray(unary_op->inputs[0]); in Run() local 186 CHECK(input_array.buffer); in Run() 198 if (cast_op->src_data_type != input_array.buffer->type) { in Run() 205 if (input_array.buffer->type != ArrayDataType::kFloat) { in Run() 208 input_float_data = &(input_array.GetBuffer<ArrayDataType::kFloat>().data); in Run() 219 const Shape& input_shape = input_array.shape(); in Run() 224 if (input_array.buffer->type == ArrayDataType::kFloat) { in Run() [all …]
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H A D | hardcode_min_max.cc | 37 const auto& input_array = model->GetArray(op->inputs[0]); in HardcodeMinMaxForIm2colArray() local 38 if (!input_array.minmax) { in HardcodeMinMaxForIm2colArray() 41 const auto& input_minmax = input_array.GetMinMax(); in HardcodeMinMaxForIm2colArray() 54 const auto& input_array = model->GetArray(op->inputs[0]); in HardcodeMinMaxForL2Normalization() local 55 if (!input_array.minmax) { in HardcodeMinMaxForL2Normalization() 58 const auto& input_minmax = input_array.GetMinMax(); in HardcodeMinMaxForL2Normalization() 156 auto& input_array = model->GetArray(op->inputs[1]); in HardcodeMinMaxForSplit() local 157 if (!input_array.minmax) { in HardcodeMinMaxForSplit() 163 if (!array.minmax || !(array.GetMinMax() == input_array.GetMinMax())) { in HardcodeMinMaxForSplit() 165 array.GetOrCreateMinMax() = *input_array.minmax; in HardcodeMinMaxForSplit() [all …]
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H A D | resolve_constant_strided_slice.cc | 28 void StridedSlice(StridedSliceOperator const& op, Array const& input_array, in StridedSlice() argument 35 CHECK(input_array.data_type == Type); in StridedSlice() 51 Shape const& input_shape = input_array.shape(); in StridedSlice() 52 Buffer<Type> const& input_buffer = input_array.GetBuffer<Type>(); in StridedSlice() 62 strided_slice_params, ToRuntimeShape(input_array.shape()), axis); in StridedSlice() 65 strided_slice_params, ToRuntimeShape(input_array.shape()), axis, in StridedSlice() 132 const auto& input_array = model->GetArray(op->inputs[0]); in Run() local 133 if (!input_array.has_shape()) { in Run() 145 StridedSlice<ArrayDataType::kFloat>(*op, input_array, &output_array); in Run() 148 StridedSlice<ArrayDataType::kUint8>(*op, input_array, &output_array); in Run() [all …]
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H A D | resolve_constant_tile.cc | 73 inline void Tile(const Array& input_array, const Array& multiples_array, in Tile() argument 82 input_array.shape(), input_array.GetBuffer<Type>().data.data(), in Tile() 88 input_array.shape(), input_array.GetBuffer<Type>().data.data(), in Tile() 129 const Array& input_array = model->GetArray(op->inputs[0]); in Run() local 135 CopyMinMaxAndQuantizationRelatedFields(input_array, &output_array); in Run() 140 Tile<ArrayDataType::kFloat>(input_array, multiples_array, &output_array); in Run() 143 Tile<ArrayDataType::kUint8>(input_array, multiples_array, &output_array); in Run() 146 Tile<ArrayDataType::kInt16>(input_array, multiples_array, &output_array); in Run() 149 Tile<ArrayDataType::kInt32>(input_array, multiples_array, &output_array); in Run() 152 Tile<ArrayDataType::kInt64>(input_array, multiples_array, &output_array); in Run() [all …]
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H A D | resolve_constant_slice.cc | 27 bool Slice(SliceOperator const& op, Array const& input_array, in Slice() argument 31 CHECK(input_array.data_type == Type); in Slice() 33 const auto& input_data = input_array.GetBuffer<Type>().data; in Slice() 57 dim_size = input_array.shape().dims()[i] - begin[i]; in Slice() 66 Shape padded_shape = input_array.shape(); in Slice() 118 const auto& input_array = model->GetArray(op->inputs[0]); in Run() local 119 if (!input_array.has_shape()) { in Run() 131 if (!Slice<ArrayDataType::kFloat>(*op, input_array, &output_array)) { in Run() 136 if (!Slice<ArrayDataType::kUint8>(*op, input_array, &output_array)) { in Run() 141 if (!Slice<ArrayDataType::kInt32>(*op, input_array, &output_array)) { in Run() [all …]
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H A D | dequantize.cc | 58 for (auto& input_array : *model->flags.mutable_input_arrays()) { in ClearArrayQuantizationParams() 59 if (input_array.name() == array_name) { in ClearArrayQuantizationParams() 63 if (input_array.has_std_value()) { in ClearArrayQuantizationParams() 64 CHECK_LE(std::abs(new_std_value - input_array.std_value()), 0.001); in ClearArrayQuantizationParams() 66 input_array.set_std_value(new_std_value); in ClearArrayQuantizationParams() 68 if (input_array.has_mean_value()) { in ClearArrayQuantizationParams() 69 CHECK_LE(std::abs(new_mean_value - input_array.mean_value()), 0.001); in ClearArrayQuantizationParams() 71 input_array.set_mean_value(new_mean_value); in ClearArrayQuantizationParams() 196 auto& input_array = model->GetArray(op->inputs[0]); in Run() local 197 if (input_array.data_type == ArrayDataType::kFloat) { in Run() [all …]
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H A D | resolve_constant_gather.cc | 28 inline void Gather(const Array& input_array, const Array& coords_array, in Gather() argument 30 const Shape& input_shape = input_array.shape(); in Gather() 32 input_array.GetBuffer<Type>().data; in Gather() 106 const Array& input_array = model->GetArray(op->inputs[0]); in Run() local 114 if (input_array.minmax) { in Run() 115 const auto& input_minmax = input_array.GetMinMax(); in Run() 124 Gather<ArrayDataType::kFloat>(input_array, coords_array, &output_array); in Run() 127 Gather<ArrayDataType::kUint8>(input_array, coords_array, &output_array); in Run() 130 Gather<ArrayDataType::kInt32>(input_array, coords_array, &output_array); in Run() 133 Gather<ArrayDataType::kInt64>(input_array, coords_array, &output_array); in Run() [all …]
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H A D | shuffle_fc_weights.cc | 40 const Array& input_array = model->GetArray(fc_op->inputs[0]); in Run() local 47 if (input_array.data_type != ArrayDataType::kUint8 || in Run() 50 !input_array.quantization_params || !weights_array.quantization_params || in Run() 55 if (!input_array.has_shape() || !weights_array.has_shape()) { in Run() 60 const Shape& input_shape = input_array.shape(); in Run() 152 shuffled_input_workspace_array.data_type = input_array.data_type; in Run() 153 *shuffled_input_workspace_array.mutable_shape() = input_array.shape(); in Run() 154 shuffled_input_workspace_array.GetOrCreateMinMax() = input_array.GetMinMax(); in Run() 156 input_array.GetQuantizationParams(); in Run()
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H A D | resolve_constant_transpose.cc | 29 void Transpose(Model* model, const Array& input_array, in Transpose() argument 31 const Shape& input_shape = input_array.shape(); in Transpose() 33 input_array.GetBuffer<Type>().data; in Transpose() 132 const Array& input_array = model->GetArray(op->inputs[0]); in Run() local 134 CopyMinMaxAndQuantizationRelatedFields(input_array, &output_array); in Run() 147 Transpose<ArrayDataType::kFloat>(model, input_array, op->perm, in Run() 151 Transpose<ArrayDataType::kUint8>(model, input_array, op->perm, in Run() 155 Transpose<ArrayDataType::kInt32>(model, input_array, op->perm, in Run() 159 Transpose<ArrayDataType::kInt64>(model, input_array, op->perm, in Run() 163 Transpose<ArrayDataType::kComplex64>(model, input_array, op->perm, in Run()
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H A D | unroll_batch_matmul.cc | 41 const Array& input_array, Model* model, in SliceInput() argument 43 int rank = input_array.shape().dimensions_count(); in SliceInput() 44 int num_rows = input_array.shape().dims(rank - 2); in SliceInput() 45 int num_cols = input_array.shape().dims(rank - 1); in SliceInput() 55 reshape_op_output.data_type = input_array.data_type; in SliceInput() 74 slice_op_output.data_type = input_array.data_type; in SliceInput() 87 slice_reshape_op_output.data_type = input_array.data_type; in SliceInput() 95 std::vector<int32> GetTransposePerm(const Array& input_array) { in GetTransposePerm() argument 96 const int32_t dims = input_array.shape().dimensions_count(); in GetTransposePerm() 117 const auto& input_array = model->GetArray(input); in TransposeInput() local [all …]
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H A D | resolve_constant_concatenation.cc | 41 for (Array* input_array : input_arrays) { in CopyTensorSegments() 42 if (!input_array->buffer) { in CopyTensorSegments() 61 for (Array* input_array : input_arrays) { in CopyTensorSegments() 62 src_ptr.push_back(input_array->GetBuffer<A>().data.data()); in CopyTensorSegments() 91 for (Array* input_array : input_arrays) { in ConcatenateTensorBuffers() 92 const Shape array_shape = input_array->shape(); in ConcatenateTensorBuffers() 120 for (Array* input_array : input_arrays) { in SetMinMaxForConcatenedArray() 123 if (!input_array->minmax) return; in SetMinMaxForConcatenedArray() 124 const MinMax& input_minmax = input_array->GetMinMax(); in SetMinMaxForConcatenedArray()
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/aosp_15_r20/external/tensorflow/tensorflow/python/kernel_tests/strings_ops/ |
H A D | reduce_join_op_test.py | 97 input_array, argument 115 inputs=input_array, 124 def _testMultipleReduceJoin(self, input_array, axis, separator=" "): argument 138 inputs=input_array, axis=axis, keep_dims=False, separator=separator) 140 inputs=input_array, axis=axis, keep_dims=True, separator=separator) 142 truth = input_array 159 input_array = ["this", "is", "a", "test"] 162 self._testReduceJoin(input_array, truth, truth_shape, axis=0) 165 input_array = [["this", "is", "a", "test"], 172 input_array, truth_dim_zero, truth_shape_dim_zero, axis=0) [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/lite/python/optimize/ |
H A D | calibrator.py | 80 input_array = [] 86 input_array.append(inputs[input_name]) 87 return input_array 103 input_array = self._create_input_array_from_dict( 110 input_array = self._create_input_array_from_dict(None, sample) 113 input_array = sample 126 self._calibrator.Prepare([list(s.shape) for s in input_array], 129 self._calibrator.Prepare([list(s.shape) for s in input_array]) 136 self._calibrator.FeedTensor(input_array, signature_key) 138 self._calibrator.FeedTensor(input_array)
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/aosp_15_r20/frameworks/rs/toolkit/ |
H A D | JniEntryPoints.cpp | 225 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, jint vectorSize, in Java_android_renderscript_toolkit_Toolkit_nativeBlur() argument 229 ByteArrayGuard input{env, input_array}; in Java_android_renderscript_toolkit_Toolkit_nativeBlur() 248 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_android_renderscript_toolkit_Toolkit_nativeColorMatrix() argument 253 ByteArrayGuard input{env, input_array}; in Java_android_renderscript_toolkit_Toolkit_nativeColorMatrix() 277 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, jint vectorSize, in Java_android_renderscript_toolkit_Toolkit_nativeConvolve() argument 282 ByteArrayGuard input{env, input_array}; in Java_android_renderscript_toolkit_Toolkit_nativeConvolve() 320 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_android_renderscript_toolkit_Toolkit_nativeHistogram() argument 324 ByteArrayGuard input{env, input_array}; in Java_android_renderscript_toolkit_Toolkit_nativeHistogram() 343 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_android_renderscript_toolkit_Toolkit_nativeHistogramDot() argument 348 ByteArrayGuard input{env, input_array}; in Java_android_renderscript_toolkit_Toolkit_nativeHistogramDot() [all …]
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/aosp_15_r20/external/renderscript-intrinsics-replacement-toolkit/renderscript-toolkit/src/main/cpp/ |
H A D | JniEntryPoints.cpp | 225 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, jint vectorSize, in Java_com_google_android_renderscript_Toolkit_nativeBlur() argument 229 ByteArrayGuard input{env, input_array}; in Java_com_google_android_renderscript_Toolkit_nativeBlur() 248 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_com_google_android_renderscript_Toolkit_nativeColorMatrix() argument 253 ByteArrayGuard input{env, input_array}; in Java_com_google_android_renderscript_Toolkit_nativeColorMatrix() 277 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, jint vectorSize, in Java_com_google_android_renderscript_Toolkit_nativeConvolve() argument 282 ByteArrayGuard input{env, input_array}; in Java_com_google_android_renderscript_Toolkit_nativeConvolve() 320 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_com_google_android_renderscript_Toolkit_nativeHistogram() argument 324 ByteArrayGuard input{env, input_array}; in Java_com_google_android_renderscript_Toolkit_nativeHistogram() 343 JNIEnv* env, jobject /*thiz*/, jlong native_handle, jbyteArray input_array, in Java_com_google_android_renderscript_Toolkit_nativeHistogramDot() argument 348 ByteArrayGuard input{env, input_array}; in Java_com_google_android_renderscript_Toolkit_nativeHistogramDot() [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/lite/python/ |
H A D | convert.py | 689 input_array = model_flags.input_arrays.add() 692 input_array.mean_value, input_array.std_value = ( 699 input_array.name = name 700 input_array.shape.dims.extend(list(map(int, shape))) 749 input_array = model_flags.input_arrays.add() 751 input_array.name = input_tensor.name 753 input_array.name = util.get_tensor_name(input_tensor) 754 input_array.data_type = convert_tensor_tf_type_to_tflite_type( 759 input_array.mean_value, input_array.std_value = ( 781 input_array.shape.dims.extend(dims) [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/compiler/tests/ |
H A D | spacetobatch_op_test.py | 27 def space_to_batch_direct(input_array, block_shape, paddings): argument 40 input_array = np.array(input_array) 45 padded = np.pad(input_array, 47 (input_array.ndim - 1 - num_block_dims)), 49 reshaped_padded_shape = [input_array.shape[0]] 50 output_shape = [input_array.shape[0] * np.prod(block_shape)] 56 reshaped_padded_shape.extend(input_array.shape[num_block_dims + 1:]) 57 output_shape.extend(input_array.shape[num_block_dims + 1:]) 63 np.arange(input_array.ndim - num_block_dims - 1) + 1 + num_block_dims
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/aosp_15_r20/external/tensorflow/tensorflow/lite/toco/ |
H A D | tooling_util.cc | 102 for (const auto& input_array : model.flags.input_arrays()) { in IsInputArray() local 103 if (array_name == input_array.name()) { in IsInputArray() 872 for (const auto& input_array : model_flags.input_arrays()) { in CheckInputArraysAreNotOutputArrays() local 874 QCHECK_NE(input_array.name(), output_array) in CheckInputArraysAreNotOutputArrays() 908 for (const auto& input_array : model_flags.input_arrays()) { in CheckNonAsciiIOArrays() local 909 QCHECK(IsAsciiPrintable(input_array.name())) in CheckNonAsciiIOArrays() 911 << input_array.name() in CheckNonAsciiIOArrays() 914 << DumpAscii(input_array.name()); in CheckNonAsciiIOArrays() 1494 for (const auto& input_array : model->flags.input_arrays()) { in CreateOrCheckRnnStateArray() local 1497 if (input_array.name() == name || num_dims == -1) { in CreateOrCheckRnnStateArray() [all …]
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