| /external/tensorflow/tensorflow/core/kernels/ |
| meta_support.h | 71 const quint8* a_data, const quint8* b_data, qint32* c_data,
81 float output_max, quint8* output);
85 void Dequantize(OpKernelContext* context, const quint8* input, int count,
91 float range_max, quint8* output);
98 void QuantizedBiasAdd(OpKernelContext* context, const quint8* input,
99 int input_count, const quint8* bias, int bias_count,
106 void Clamp(OpKernelContext* context, const quint8* input, int input_count,
107 quint8 clamp_min, quint8 clamp_max, quint8* output)
[all...] |
| quantized_reshape_op_test.cc | 55 input.flat<quint8>()(i) = quint8(i);
56 expected.flat<quint8>()(i) = quint8(i);
58 AddInputFromArray<quint8>(input.shape(), input.flat<quint8>());
66 test::ExpectTensorEqual<quint8>(expected, *GetOutput(0));
|
| quantized_batch_norm_op_test.cc | 72 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
78 FloatTensorToQuantized<quint8>(mean_float, mean_min, mean_max);
83 Tensor variance_quantized = FloatTensorToQuantized<quint8>(
90 FloatTensorToQuantized<quint8>(beta_float, beta_min, beta_max);
96 FloatTensorToQuantized<quint8>(gamma_float, gamma_min, gamma_max);
98 AddInputFromArray<quint8>(input_quantized.shape(),
99 input_quantized.flat<quint8>());
102 AddInputFromArray<quint8>(mean_quantized.shape(),
103 mean_quantized.flat<quint8>());
106 AddInputFromArray<quint8>(variance_quantized.shape()
[all...] |
| quantized_pooling_ops_test.cc | 45 .Attr("T", DataTypeToEnum<quint8>::v())
62 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
70 AddInputFromArray<quint8>(input_quantized.shape(),
71 input_quantized.flat<quint8>());
79 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max);
90 .Attr("T", DataTypeToEnum<quint8>::v())
107 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
115 AddInputFromArray<quint8>(input_quantized.shape(),
116 input_quantized.flat<quint8>());
124 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max)
[all...] |
| quantized_activation_ops.cc | 42 if (meta::IsSupportedAndEnabled() && std::is_same<T, quint8>()) {
43 auto input_ui8_array = input.flat<quint8>();
45 min_as_quantized, 255, output->flat<quint8>().data());
76 if (meta::IsSupportedAndEnabled() && std::is_same<T, quint8>()) {
77 auto input_ui8_array = input.flat<quint8>();
80 output->flat<quint8>().data());
105 .TypeConstraint<quint8>("Tinput")
106 .TypeConstraint<quint8>("out_type"),
107 QuantizedReluOp<quint8>);
116 .TypeConstraint<quint8>("Tinput"
[all...] |
| quantized_bias_add_op_test.cc | 59 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
67 FloatTensorToQuantized<quint8>(bias_float, bias_min, bias_max);
73 AddInputFromArray<quint8>(input_quantized.shape(),
74 input_quantized.flat<quint8>());
75 AddInputFromArray<quint8>(bias_quantized.shape(),
76 bias_quantized.flat<quint8>());
119 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
139 FloatTensorToQuantized<quint8>(bias_float, bias_min, bias_max);
155 AddInputFromArray<quint8>(input_quantized.shape(),
156 input_quantized.flat<quint8>());
[all...] |
| quantized_activation_ops_test.cc | 52 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
56 AddInputFromArray<quint8>(input_quantized.shape(),
57 input_quantized.flat<quint8>());
65 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max);
83 FloatTensorToQuantized<quint8>(input_float, input_min, input_max);
87 AddInputFromArray<quint8>(input_quantized.shape(),
88 input_quantized.flat<quint8>());
96 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max);
|
| quantized_bias_add_op.cc | 67 if (meta::IsSupportedAndEnabled() && std::is_same<T1, quint8>() &&
68 std::is_same<T2, quint8>() && std::is_same<T3, qint32>()) {
69 auto input_ui8_array = input.flat<quint8>();
70 auto bias_ui8_array = bias.flat<quint8>();
96 .TypeConstraint<quint8>("T1")
97 .TypeConstraint<quint8>("T2")
99 QuantizedBiasAddOp<quint8, quint8, qint32>);
|
| quantization_utils_test.cc | 39 std::vector<quint8> expected_values;
42 expected_values.push_back(FloatToQuantized<quint8>(
50 auto output_values = o_tensor.flat<quint8>();
58 RequantizeManyInNewRangeUsingEigen<qint32, quint8>(
78 const std::vector<quint8>& values_quantized,
90 tensorflow::test::AsTensor(gtl::ArraySlice<quint8>(values_quantized));
94 const auto input_array = i_tensor.flat<quint8>();
190 std::vector<quint8> values_quantized;
193 values_quantized.push_back(FloatToQuantized<quint8>(v, r[0], r[1]));
199 int low = Eigen::NumTraits<quint8>::lowest()
[all...] |
| quantized_matmul_op_test.cc | 58 AddInputFromArray<quint8>(TensorShape({2, 3}), {1, 2, 3, 4, 5, 6});
63 AddInputFromArray<quint8>(TensorShape({3, 4}),
116 AddInputFromArray<quint8>(TensorShape({a_rows, a_cols}), {11});
120 AddInputFromArray<quint8>(TensorShape({b_rows, b_cols}), {0});
160 AddInputFromArray<quint8>(TensorShape({a_rows, a_cols}), {11});
164 AddInputFromArray<quint8>(TensorShape({b_rows, b_cols}), {0});
209 AddInputFromArray<quint8>(TensorShape({a_rows, a_cols}), {
228 AddInputFromArray<quint8>(TensorShape({b_rows, b_cols}), {
305 Tensor a_quantized = FloatTensorToQuantized<quint8>(a_float, a_min, a_max);
325 Tensor b_quantized = FloatTensorToQuantized<quint8>(b_float, b_min, b_max)
[all...] |
| quantized_conv_ops_test.cc | 74 FloatTensorToQuantized<quint8>(image_float, image_min, image_max);
88 FloatTensorToQuantized<quint8>(filter_float, filter_min, filter_max);
90 AddInputFromArray<quint8>(image_quantized.shape(),
91 image_quantized.flat<quint8>());
92 AddInputFromArray<quint8>(filter_quantized.shape(),
93 filter_quantized.flat<quint8>());
153 AddInputFromArray<quint8>(
158 AddInputFromArray<quint8>(
196 AddInputFromArray<quint8>(
201 AddInputFromArray<quint8>(
[all...] |
| quantize_op_test.cc | 36 .Attr("T", DataTypeToEnum<quint8>::v())
50 test::FillValues<quint8>(&expected, {0, 1, 1, 2, 127, 255, 255});
51 test::ExpectTensorEqual<quint8>(expected, *GetOutput(0));
59 .Attr("T", DataTypeToEnum<quint8>::v())
70 // we are performing quantization by scaling to quint8.
74 test::FillValues<quint8>(&expected, {0, 0, 1, 1, 2, 127, 255, 255});
75 test::ExpectTensorEqual<quint8>(expected, *GetOutput(0));
91 .Attr("T", DataTypeToEnum<quint8>::v())
101 // we are performing quantization by scaling to quint8.
103 // Input element 2.0 should map to max quint8 value 255
[all...] |
| requantize.cc | 78 std::is_same<T2, quint8>()) {
83 output->flat<quint8>().data());
100 .TypeConstraint<quint8>("out_type"),
101 RequantizeOp<qint32, quint8>);
|
| quantize_down_and_shrink_range_op_test.cc | 44 .Attr("out_type", DataTypeToEnum<quint8>::v())
60 test::FillValues<quint8>(&expected, {0, 127, 255});
61 test::ExpectTensorEqual<quint8>(expected, *GetOutput(0));
|
| quantized_resize_bilinear_op.cc | 131 inline uint8x8_t ToUint8x8(const quint8* v0, const quint8* v1, const quint8* v2,
132 const quint8* v3, const quint8* v4, const quint8* v5,
133 const quint8* v6, const quint8* v7) {
194 const quint8* tl0, const quint8* tr0, const quint8* bl0, const quint8* br0
[all...] |
| quantized_instance_norm_test.cc | 28 void ReferenceImpl(const quint8* inp, float inp_min, float inp_max,
107 ReferenceImpl(input.flat<quint8>().data(), x_min, x_max, input.shape(),
110 auto out = outputs[0].flat<quint8>();
126 auto input = input_tensor.flat<quint8>();
128 input = input.random(Eigen::internal::UniformRandomGenerator<quint8>());
135 auto input = input_tensor.flat<quint8>();
145 auto input = input_tensor.flat<quint8>();
156 auto input = input_tensor.flat<quint8>();
157 input = input.random(Eigen::internal::UniformRandomGenerator<quint8>());
164 auto input = input_tensor.flat<quint8>();
[all...] |
| quantized_matmul_op.cc | 35 void GemmlowpMultiply(OpKernelContext* op_context, const quint8* a_data,
36 const quint8* b_data, qint32* c_data, int m, int n, int k,
135 if (meta::IsSupportedAndEnabled() && std::is_same<T1, quint8>() &&
136 std::is_same<T2, quint8>() && std::is_same<Toutput, qint32>() &&
143 } else if (std::is_same<T1, quint8>() && std::is_same<T2, quint8>() &&
196 .TypeConstraint<quint8>("T1")
197 .TypeConstraint<quint8>("T2")
199 QuantizedMatMulOp<quint8, quint8, qint32>)
[all...] |
| quantized_add_op.cc | 63 void ScalarAddition(OpKernelContext* context, const quint8* full_input,
65 int64 num_elements, quint8 scalar_input,
68 const int32 scalar_in_output_range = RequantizeInNewRange<quint8, qint32>(
72 QuantizedToFloat<quint8>(0, full_input_min, full_input_max);
74 QuantizedToFloat<quint8>(1, full_input_min, full_input_max);
120 void ScalarAddition(OpKernelContext* context, const quint8* full_input,
122 int64 num_elements, quint8 scalar_input,
125 const int32 scalar_in_output_range = RequantizeInNewRange<quint8, qint32>(
129 QuantizedToFloat<quint8>(0, full_input_min, full_input_max);
131 QuantizedToFloat<quint8>(1, full_input_min, full_input_max)
[all...] |
| requantize_op_test.cc | 41 .Attr("out_type", DataTypeToEnum<quint8>::v())
62 test::FillValues<quint8>(&expected, {0, 128, 255});
63 test::ExpectTensorEqual<quint8>(expected, *GetOutput(0));
|
| quantize_down_and_shrink_range.cc | 84 std::is_same<T2, quint8>()) {
88 actual_max_float, output->flat<quint8>().data());
104 .TypeConstraint<quint8>("out_type"),
105 QuantizeDownAndShrinkRangeOp<qint32, quint8>);
|
| quantized_concat_op_test.cc | 73 .Attr("T", DataTypeToEnum<quint8>::v())
83 FloatTensorToQuantized<quint8>(first_float, first_min, first_max);
92 FloatTensorToQuantized<quint8>(second_float, second_min, second_max);
101 AddInputFromArray<quint8>(first_quantized.shape(),
102 first_quantized.flat<quint8>());
103 AddInputFromArray<quint8>(second_quantized.shape(),
104 second_quantized.flat<quint8>());
114 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max);
201 .Attr("T", DataTypeToEnum<quint8>::v())
211 FloatTensorToQuantized<quint8>(first_float, first_min, first_max)
[all...] |
| meta_support.cc | 118 void QuantizedGemmImpl(OpKernelContext* tf_context, const quint8* a_data,
119 const quint8* b_data, qint32* c_data, int m, int n,
221 bool transpose_b, const quint8* a_data, const quint8* b_data,
258 float output_max, quint8* output) {
292 void Dequantize(OpKernelContext* tf_context, const quint8* input, int count,
317 float range_min, float range_max, quint8* output) {
346 void QuantizedBiasAdd(OpKernelContext* tf_context, const quint8* input,
347 int input_count, const quint8* bias, int bias_count,
385 void Clamp(OpKernelContext* tf_context, const quint8* input, int count
[all...] |
| quantized_mul_op.cc | 51 void ScalarMultiply<quint8, qint32>(OpKernelContext* context,
52 const quint8* full_input,
54 quint8 scalar_input,
125 void VectorMultiply<quint8, qint32>(OpKernelContext* context,
126 const quint8* x_data, int32 offset_x,
127 const quint8* y_data, int32 offset_y,
203 void VectorTensorMultiply<quint8, qint32>(
204 const quint8* vector_data, int32 vector_offset, int64 vector_num_elements,
205 const quint8* tensor_data, int32 tensor_offset, int64 tensor_num_elements,
388 .TypeConstraint<quint8>("T1"
[all...] |
| /external/tensorflow/tensorflow/core/framework/ |
| type_traits.h | 43 struct is_quantized<quint8> : true_type {};
83 class numeric_limits<tensorflow::quint8>
99 struct is_signed<tensorflow::quint8> : public is_signed<tensorflow::uint8> {};
|
| /external/tensorflow/tensorflow/python/ops/ |
| dequantize_op_test.py | 42 dtypes.quint8: np.uint8,
63 self._testDequantizeOp(np.array([0, 128, 255]), 0.0, 6.0, dtypes.quint8)
64 self._testDequantizeOp(np.array([0, 128, 255]), 0.0, 123.456, dtypes.quint8)
66 np.array([0, 4, 42, 108, 243]), 5.0, 200.2, dtypes.quint8)
|
