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Searched refs:qint32 (Results 1 – 25 of 98) sorted by relevance

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/external/tensorflow/tensorflow/core/kernels/
Dquantization_utils_test.cc36 const std::vector<qint32>& values_quantized, in TestRequantizeMany()
48 tensorflow::test::AsTensor(gtl::ArraySlice<qint32>(values_quantized)); in TestRequantizeMany()
53 auto input_array = i_tensor.flat<qint32>(); in TestRequantizeMany()
58 RequantizeManyInNewRangeUsingEigen<qint32, quint8>( in TestRequantizeMany()
81 std::vector<qint32> expected_values; in TestRequantizeMany8To32Bit()
84 expected_values.push_back(FloatToQuantized<qint32>( in TestRequantizeMany8To32Bit()
92 auto output_values = o_tensor.flat<qint32>(); in TestRequantizeMany8To32Bit()
101 const qint32 e = expected_values[value_index]; in TestRequantizeMany8To32Bit()
102 const qint32 v = output_values(value_index); in TestRequantizeMany8To32Bit()
132 std::vector<qint32> values_quantized; in TestRequantizeManyInNewRange32To8Bit()
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Dquantized_add_op.cc66 float output_min, float output_max, qint32* output) { in ScalarAddition()
67 const int32 scalar_in_output_range = RequantizeInNewRange<quint8, qint32>( in ScalarAddition()
75 FloatToQuantizedUnclamped<qint32>(input_0_float, output_min, output_max); in ScalarAddition()
77 FloatToQuantizedUnclamped<qint32>(input_1_float, output_min, output_max); in ScalarAddition()
81 static_cast<int64>(Eigen::NumTraits<qint32>::lowest()); in ScalarAddition()
83 static_cast<int64>(Eigen::NumTraits<qint32>::highest()); in ScalarAddition()
123 float output_min, float output_max, qint32* output) { in ScalarAddition()
124 const int32 scalar_in_output_range = RequantizeInNewRange<quint8, qint32>( in ScalarAddition()
132 FloatToQuantizedUnclamped<qint32>(input_0_float, output_min, output_max); in ScalarAddition()
134 FloatToQuantizedUnclamped<qint32>(input_1_float, output_min, output_max); in ScalarAddition()
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Drequantization_range_op_test.cc33 void CalculateUsedRange(const Tensor& input, qint32* actual_min_quantized,
34 qint32* actual_max_quantized);
47 .Attr("Tinput", DataTypeToEnum<qint32>::v()) in TEST_F()
57 AddInputFromArray<qint32>(TensorShape({value_count}), in TEST_F()
74 test::FillFn<qint32>(&quantized_tensor, [](int n) { return qint32(n); }); in BM_RequantizationRange()
76 qint32 actual_min; in BM_RequantizationRange()
77 qint32 actual_max; in BM_RequantizationRange()
Drequantization_range_op.cc34 void CalculateUsedRange(const Tensor& input, qint32* used_min_quantized, in CalculateUsedRange()
35 qint32* used_max_quantized) { in CalculateUsedRange()
36 auto input_array = input.flat<qint32>(); in CalculateUsedRange()
37 Eigen::Tensor<qint32, 0, Eigen::RowMajor> min = input_array.minimum(); in CalculateUsedRange()
38 Eigen::Tensor<qint32, 0, Eigen::RowMajor> max = input_array.maximum(); in CalculateUsedRange()
56 qint32 used_min_quantized; in Compute()
57 qint32 used_max_quantized; in Compute()
75 .TypeConstraint<qint32>("Tinput"),
Dquantized_matmul_op_test.cc52 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
81 test::FillValues<qint32>(&expected, {74, 80, 86, 92, 173, 188, 203, 218}); in TEST_F()
82 test::ExpectTensorEqual<qint32>(expected, *GetOutput(0)); in TEST_F()
103 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
131 test::FillValues<qint32>(&expected, {-1}); in TEST_F()
132 test::ExpectTensorEqual<qint32>(expected, *GetOutput(0)); in TEST_F()
153 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
193 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
256 test::FillValues<qint32>(&expected, { in TEST_F()
266 test::ExpectTensorEqual<qint32>(expected, *GetOutput(0)); in TEST_F()
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Dquantized_concat_op_test.cc138 .Attr("T", DataTypeToEnum<qint32>::v()) in TestSmall32Bit()
148 FloatTensorToQuantized<qint32>(first_float, first_min, first_max); in TestSmall32Bit()
157 FloatTensorToQuantized<qint32>(second_float, second_min, second_max); in TestSmall32Bit()
167 AddInputFromArray<qint32>(first_quantized.shape(), in TestSmall32Bit()
168 first_quantized.flat<qint32>()); in TestSmall32Bit()
169 AddInputFromArray<qint32>(second_quantized.shape(), in TestSmall32Bit()
170 second_quantized.flat<qint32>()); in TestSmall32Bit()
180 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TestSmall32Bit()
288 ConcatHelper<qint32>(state, 0 /* concat_dimension */, true /* same_limits */, in BM_QConcatDim0SameLimitQInt32()
295 ConcatHelper<qint32>(state, 1 /* concat_dimension */, true /* same_limits */, in BM_QConcatDim1SameLimitQInt32()
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Dquantized_conv_ops_test.cc51 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
130 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TEST_F()
143 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
171 test::FillValues<qint32>( in TEST_F()
174 test::ExpectTensorEqual<qint32>(expected, *GetOutput(0)); in TEST_F()
186 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
214 test::FillValues<qint32>(&expected, {348, 252, 274, 175}); in TEST_F()
215 test::ExpectTensorEqual<qint32>(expected, *GetOutput(0)); in TEST_F()
227 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
257 test::FillValues<qint32>(&expected, {348, 252, 274, 175, // in TEST_F()
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Drequantize.cc76 if (meta::IsSupportedAndEnabled() && std::is_same<T1, qint32>() && in Compute()
78 auto input_i32_array = input.flat<qint32>(); in Compute()
98 .TypeConstraint<qint32>("Tinput")
100 RequantizeOp<qint32, quint8>);
104 .TypeConstraint<qint32>("Tinput")
106 RequantizeOp<qint32, qint8>);
Dquantized_bias_add_op.cc68 std::is_same<T2, quint8>() && std::is_same<T3, qint32>()) { in Compute()
77 output->flat<qint32>().data()); in Compute()
98 .TypeConstraint<qint32>("out_type"),
99 QuantizedBiasAddOp<quint8, quint8, qint32>);
104 .TypeConstraint<qint32>("out_type"),
105 QuantizedBiasAddOp<qint8, qint8, qint32>);
Dquantized_activation_ops.cc100 .TypeConstraint<qint32>("Tinput")
101 .TypeConstraint<qint32>("out_type"),
102 QuantizedReluOp<qint32>);
111 .TypeConstraint<qint32>("Tinput")
112 .TypeConstraint<qint32>("out_type"),
113 QuantizedRelu6Op<qint32>);
Dquantized_resize_bilinear_op_test.cc249 image_quantized_tensor.flat<qint32>()(i) = in TestResizeBilinearOneDim()
250 FloatToQuantized<qint32>(static_cast<float>(i), MIN, MAX); in TestResizeBilinearOneDim()
264 QuantizedToFloat<qint32>(outputs.at(0).flat<qint32>()(i), MIN, MAX); in TestResizeBilinearOneDim()
267 expected_val = QuantizedToFloat<qint32>( in TestResizeBilinearOneDim()
268 image_quantized_tensor.flat<qint32>()(i / 2), MIN, MAX); in TestResizeBilinearOneDim()
270 const float image_val0 = QuantizedToFloat<qint32>( in TestResizeBilinearOneDim()
271 image_quantized_tensor.flat<qint32>()(i / 2), MIN, MAX); in TestResizeBilinearOneDim()
272 const float image_val1 = QuantizedToFloat<qint32>( in TestResizeBilinearOneDim()
273 image_quantized_tensor.flat<qint32>()(i / 2 + 1), MIN, MAX); in TestResizeBilinearOneDim()
282 CheckTensorValue<qint32>(image_quantized_tensor.flat<qint32>().data(), in TestResizeBilinearOneDim()
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Dquantized_resize_bilinear_op.cc167 inline int32x2_t ToInt32x2(const qint32* v0, const qint32* v1) { in ToInt32x2()
178 const qint32* top_left0, const qint32* top_right0, in ComputeLerpx2()
179 const qint32* bottom_left0, const qint32* bottom_right0, in ComputeLerpx2()
180 const qint32* top_left1, const qint32* top_right1, in ComputeLerpx2()
181 const qint32* bottom_left1, const qint32* bottom_right1, in ComputeLerpx2()
337 const qint32* const ys_input_lower_ptr, in OutputLerp32x4x1()
338 const qint32* const ys_input_upper_ptr, in OutputLerp32x4x1()
339 qint32* output_y_ptr) { in OutputLerp32x4x1()
374 OutputLerpForChannels<RESOLUTION, qint32, int32, int64>( in OutputLerp32x4x1()
385 const qint32* const ys_input_lower_ptr, in OutputLerp32x4x3()
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Drequantize_op_test.cc40 .Attr("Tinput", DataTypeToEnum<qint32>::v()) in ConfigureRequantize()
54 AddInputFromArray<qint32>(TensorShape({value_count}), in TEST_F()
72 AddInputFromArray<qint32>(TensorShape({value_count}), in TEST_F()
86 AddInputFromArray<qint32>(TensorShape({value_count}), in TEST_F()
Dquantize_down_and_shrink_range.cc83 if (meta::IsSupportedAndEnabled() && std::is_same<T1, qint32>() && in Compute()
85 auto input_i32_array = input.flat<qint32>(); in Compute()
103 .TypeConstraint<qint32>("Tinput")
105 QuantizeDownAndShrinkRangeOp<qint32, quint8>);
Dmeta_support.h71 const quint8* a_data, const quint8* b_data, qint32* c_data,
79 void Requantize(OpKernelContext* context, const qint32* input, int count,
102 qint32* output);
Dquantization_utils.h248 inline void RequantizeManyInNewRangeReference(const qint32* input, int64 count, in RequantizeManyInNewRangeReference()
296 float min_output, float max_output, qint32* output) { in RequantizeManyInNewRange8To32BitReference()
300 FloatToQuantizedUnclamped<qint32>(code_0_float, min_output, max_output); in RequantizeManyInNewRange8To32BitReference()
302 FloatToQuantizedUnclamped<qint32>(code_1_float, min_output, max_output); in RequantizeManyInNewRange8To32BitReference()
305 static_cast<int64>(Eigen::NumTraits<qint32>::lowest()); in RequantizeManyInNewRange8To32BitReference()
307 static_cast<int64>(Eigen::NumTraits<qint32>::highest()); in RequantizeManyInNewRange8To32BitReference()
320 inline void RequantizeManyInNewRangeNeon(const qint32* input, int64 count, in RequantizeManyInNewRangeNeon()
407 inline void RequantizeManyInNewRange<qint32, quint8>(
408 const qint32* input, int64 count, float min_input, float max_input,
597 inline void RequantizeManyInNewRange<quint8, qint32>(
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Dquantized_bias_add_op_test.cc48 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
86 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TEST_F()
98 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
168 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TEST_F()
/external/tensorflow/tensorflow/core/kernels/mkl/
Dmkl_qmatmul_op_test.cc87 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
88 .Attr("T", DataTypeToEnum<qint32>::v()) in TEST_F()
102 AddInputFromArray<qint32>(TensorShape({4}), {1, 2, 3, 4}); in TEST_F()
129 test::FillValues<qint32>(&expected, {75, 82, 89, 96, 174, 190, 206, 222}); in TEST_F()
135 conv_comp.ConvertMKL2TF<qint32>(DT_QINT32, output, mkl_shape_tensor, in TEST_F()
138 test::ExpectTensorEqual<qint32>(expected, output_quantized); in TEST_F()
160 .Attr("Toutput", DataTypeToEnum<qint32>::v()) in TEST_F()
161 .Attr("T", DataTypeToEnum<qint32>::v()) in TEST_F()
175 AddInputFromArray<qint32>(TensorShape({4}), {100, -200, 300, -400}); in TEST_F()
202 test::FillValues<qint32>(&expected, in TEST_F()
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Dmkl_requantize_ops_test.cc94 test::FillValues<qint32>( in Setup()
136 .Attr("T", DataTypeToEnum<qint32>::v()) in TEST_F()
142 AddInputFromArray<qint32>(input_tensor_qint32.shape(), in TEST_F()
143 input_tensor_qint32.flat<qint32>()); in TEST_F()
197 .Attr("T", DataTypeToEnum<qint32>::v()) in TEST_F()
203 AddInputFromArray<qint32>(input_tensor_qint32.shape(), in TEST_F()
204 input_tensor_qint32.flat<qint32>()); in TEST_F()
259 .Attr("T", DataTypeToEnum<qint32>::v()) in TEST_F()
265 AddInputFromArray<qint32>(input_tensor_qint32.shape(), in TEST_F()
266 input_tensor_qint32.flat<qint32>()); in TEST_F()
Dmkl_quantized_conv_ops_test.cc90 .Attr("out_type", DataTypeToEnum<qint32>::v()) in ConfigureQuantizedConv2D()
164 test::FillValues<qint32>(&expected, {229, 301, 133, 181, 483, 597, 267, in RunQuantizedDepthwiseConv2DOp()
167 test::FillValues<qint32>(&expected, {228, 300, 132, 180, 482, 596, 266, in RunQuantizedDepthwiseConv2DOp()
176 conv_comp.ConvertMklToTF<qint32>(DT_QINT32, output, output_mkl_metadata, in RunQuantizedDepthwiseConv2DOp()
179 test::ExpectTensorEqual<qint32>(expected, output_quantized); in RunQuantizedDepthwiseConv2DOp()
277 conv_comp.ConvertMklToTF<qint32>(DT_QINT32, output, output_mkl_metadata, in TEST_F()
283 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TEST_F()
318 .Attr("out_type", DataTypeToEnum<qint32>::v()) in TEST_F()
381 conv_comp.ConvertMklToTF<qint32>(DT_QINT32, output, output_mkl_metadata, in TEST_F()
387 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); in TEST_F()
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Dmkl_qmatmul_op.cc321 std::is_same<Toutput, qint32>::value) { in Compute()
344 MklQuantizationRangeForMultiplication<quint8, qint8, qint32>( in ComputeOutputRangeForInt32()
401 if (std::is_same<Tbias, qint32>::value) { in GetBiasHandle()
538 .TypeConstraint<qint32>("Toutput"),
547 .TypeConstraint<qint32>("Toutput")
549 MklDnnQuantizedMatMulOp<CPUDevice, quint8, qint8, float, qint32>);
555 .TypeConstraint<qint32>("Tbias")
556 .TypeConstraint<qint32>("Toutput")
558 MklDnnQuantizedMatMulOp<CPUDevice, quint8, qint8, qint32, qint32>);
567 .TypeConstraint<qint32>("Toutput"),
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Dmkl_conv_ops.cc1412 MklQuantizationRangeForMultiplication<Tinput, qint8, qint32>( in Compute()
1429 MklQuantizationRangeForMultiplication<Tinput, qint8, qint32>( in Compute()
1507 if (std::is_same<Tbias, qint32>::value) { in GetBiasHandle()
1845 .TypeConstraint<qint32>("out_type"),
1860 .TypeConstraint<qint32>("out_type"),
1867 .TypeConstraint<qint32>("out_type")
1869 MklQuantizedConv2DOp<CPUDevice, quint8, float, qint32,
1870 qint32, false, false>);
1877 .TypeConstraint<qint32>("out_type")
1879 MklQuantizedConv2DOp<CPUDevice, quint8, float, qint32,
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Dmkl_requantization_range_per_channel_op.cc66 auto input_matrix = input.flat_inner_dims<qint32>(); in Compute()
88 Eigen::Tensor<qint32, 0, Eigen::RowMajor> min = in Compute()
90 Eigen::Tensor<qint32, 0, Eigen::RowMajor> max = in Compute()
132 .TypeConstraint<qint32>("T"),
Dmkl_requantize_per_channel_op.cc103 memory::desc input_md = memory::desc(dims_mkl_order, MklDnnType<qint32>(), in Compute()
113 static_cast<void*>(const_cast<qint32*>(input.flat<qint32>().data())); in Compute()
174 .TypeConstraint<qint32>("T")
180 .TypeConstraint<qint32>("T")
/external/tensorflow/tensorflow/core/framework/
Dtype_traits.h45 struct is_quantized<qint32> : true_type {};
92 class numeric_limits<tensorflow::qint32>
105 struct is_signed<tensorflow::qint32> : public is_signed<tensorflow::int32> {};

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