| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | pooling_test.cc | 104 std::initializer_list<int> output_dims_data, float output_min, in TestAveragePoolingQuantized() argument
120 output_min, output_max), in TestAveragePoolingQuantized()
246 float output_min, float output_max, in TestMaxPoolQuantized() argument
263 output_min, output_max), in TestMaxPoolQuantized()
344 const float output_min = -15.9375; in TF_LITE_MICRO_TEST() local
365 F2Q(0., output_min, output_max), in TF_LITE_MICRO_TEST()
366 F2Q(0.75, output_min, output_max), in TF_LITE_MICRO_TEST()
369 output_min, output_max, // output quantization range in TF_LITE_MICRO_TEST()
378 const float output_min = -15.9375; in TF_LITE_MICRO_TEST() local
392 F2QS(-0.25, output_min, output_max), F2QS(0.75, output_min, output_max)}, in TF_LITE_MICRO_TEST()
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| D | mul_test.cc | 101 const float output_min, const float output_max, in TestMulQuantized() argument
121 output_min, output_max), in TestMulQuantized()
180 const float output_min = -1; in TF_LITE_MICRO_TEST() local
200 output_min, output_max, in TF_LITE_MICRO_TEST()
202 F2QS(-0.48, output_min, output_max), in TF_LITE_MICRO_TEST()
203 F2QS(0.08, output_min, output_max), in TF_LITE_MICRO_TEST()
204 F2QS(0.81, output_min, output_max), in TF_LITE_MICRO_TEST()
205 F2QS(0.56, output_min, output_max), in TF_LITE_MICRO_TEST()
214 const float output_min = -10; in TF_LITE_MICRO_TEST() local
234 input_min, input_max, {4, 1, 2, 2, 1}, output_min, output_max, in TF_LITE_MICRO_TEST()
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| D | fully_connected_test.cc | 104 const float output_min, const float output_max, in TestFullyConnectedQuantized() argument
122 output_min, output_max), in TestFullyConnectedQuantized()
269 const float output_min = -127.0f; in TF_LITE_MICRO_TEST() local
310 F2Q(24, output_min, output_max), F2Q(25, output_min, output_max), in TF_LITE_MICRO_TEST()
311 F2Q(26, output_min, output_max), F2Q(58, output_min, output_max), in TF_LITE_MICRO_TEST()
312 F2Q(59, output_min, output_max), F2Q(60, output_min, output_max), in TF_LITE_MICRO_TEST()
321 bias_scale, expected_output_data, output_dims_data, output_min, in TF_LITE_MICRO_TEST()
335 const float output_min = -127.0f; in TF_LITE_MICRO_TEST() local
376 F2QS(24, output_min, output_max), F2QS(25, output_min, output_max), in TF_LITE_MICRO_TEST()
377 F2QS(26, output_min, output_max), F2QS(58, output_min, output_max), in TF_LITE_MICRO_TEST()
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| D | softmax_test.cc | 93 float output_min, float output_max, in TestSoftmaxQuantized() argument
106 output_min, output_max), in TestSoftmaxQuantized()
159 std::initializer_list<int> output_dims_data, float output_min, in TestSoftmaxQuantizedSigned() argument
172 output_min, output_max), in TestSoftmaxQuantizedSigned()
258 const float output_min = 0.0f; in TF_LITE_MICRO_TEST() local
274 F2Q(0.011656231, output_min, output_max), in TF_LITE_MICRO_TEST()
275 F2Q(0.031684921, output_min, output_max), in TF_LITE_MICRO_TEST()
276 F2Q(0.086128544, output_min, output_max), in TF_LITE_MICRO_TEST()
277 F2Q(0.234121657, output_min, output_max), in TF_LITE_MICRO_TEST()
278 F2Q(0.636408647, output_min, output_max), in TF_LITE_MICRO_TEST()
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| /external/XNNPACK/src/xnnpack/ |
| D | params-init.h | 34 uint8_t output_min, in xnn_init_scalar_q8_gemm_params() argument
61 (int32_t) (uint32_t) output_min - (int32_t) (uint32_t) output_zero_point; in xnn_init_scalar_q8_gemm_params()
73 uint8_t output_min, in xnn_init_q8_gemm_params() argument
118 params.sse2.output_min[i] = output_min; in xnn_init_q8_gemm_params()
127 params.neon.output_min = output_min; in xnn_init_q8_gemm_params()
138 (int32_t) (uint32_t) output_min - (int32_t) (uint32_t) output_zero_point; in xnn_init_q8_gemm_params()
150 uint8_t output_min, in xnn_init_q8_avgpool_params() argument
189 params.sse2.output_min[i] = output_min; in xnn_init_q8_avgpool_params()
197 params.neon.output_min = output_min; in xnn_init_q8_avgpool_params()
206 (int32_t) (uint32_t) output_min - (int32_t) (uint32_t) output_zero_point; in xnn_init_q8_avgpool_params()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantized_add_op.cc | 48 float scalar_input_max, float output_min, float output_max, in ScalarAddition() argument
51 scalar_input, scalar_input_min, scalar_input_max, output_min, output_max); in ScalarAddition()
54 full_input[i], full_input_min, full_input_max, output_min, output_max); in ScalarAddition()
66 float output_min, float output_max, qint32* output) { in ScalarAddition() argument
68 scalar_input, scalar_input_min, scalar_input_max, output_min, output_max); 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()
123 float output_min, float output_max, qint32* output) { in ScalarAddition() argument
125 scalar_input, scalar_input_min, scalar_input_max, output_min, output_max); in ScalarAddition()
132 FloatToQuantizedUnclamped<qint32>(input_0_float, output_min, output_max); in ScalarAddition()
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| D | quantized_batch_norm_op.cc | 38 Tensor* output, float* output_min, float* output_max) { in ReferenceBatchNorm() argument
49 *output_min = std::numeric_limits<float>::max(); in ReferenceBatchNorm()
78 *output_min = std::min(output_value, *output_min); in ReferenceBatchNorm()
82 FloatToQuantized<T2>(output_value, *output_min, *output_max); in ReferenceBatchNorm()
101 Tensor* output, float* output_min, float* output_max) { in FixedPointBatchNorm() argument
115 *output_min = -(1 << 20); in FixedPointBatchNorm()
139 FloatToQuantized<T2>(scale_value, *output_min, *output_max); in FixedPointBatchNorm()
141 FloatToQuantized<T2>(offset_value, *output_min, *output_max); in FixedPointBatchNorm()
145 FloatToQuantized<T2>(1.0f, *output_min, *output_max); in FixedPointBatchNorm()
151 input_max, *output_min, *output_max); in FixedPointBatchNorm()
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| D | quantized_concat_op.cc | 35 float output_min, float output_max) in RequantizeCopier()
36 : output_min(output_min), in RequantizeCopier()
43 if (input_min == output_min && input_max == output_max) { in Copy()
54 FloatToQuantizedStruct<T> f2q(output_min, output_max); in Copy()
64 float output_min; member
82 float* output_min, float* output_max) { in CalculateInputAndOutputRange() argument
100 *output_min = -largest_value; in CalculateInputAndOutputRange()
103 *output_min = overall_min; in CalculateInputAndOutputRange()
192 float output_min = std::numeric_limits<float>::max(); in Compute() local
196 &input_mins_and_maxes, &output_min, in Compute()
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| D | quantize_op_test.cc | 123 auto output_min = *GetOutput(1); in TEST_P() local
127 EXPECT_EQ(output_min.flat<float>()(slice_idx), 0); in TEST_P()
203 auto output_min = *GetOutput(1); in TEST_P() local
207 EXPECT_EQ(output_min.flat<float>()(slice_idx), -128.0 * (slice_idx + 1)); in TEST_P()
253 auto output_min = *GetOutput(1); in TEST_P() local
257 EXPECT_EQ(output_min.flat<float>()(slice_idx), -128.0 * (slice_idx + 1)); in TEST_P()
415 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
417 EXPECT_NEAR(0.0f, output_min, 1e-5f); in TEST_F()
437 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
439 EXPECT_NEAR(0.0f, output_min, 1e-5f); in TEST_F()
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| D | quantized_activation_ops.cc | 51 Tensor* output_min = nullptr; in Compute() local
52 OP_REQUIRES_OK(context, context->allocate_output(1, {}, &output_min)); in Compute()
53 output_min->flat<float>()(0) = min_input; in Compute()
89 Tensor* output_min = nullptr; in Compute() local
90 OP_REQUIRES_OK(context, context->allocate_output(1, {}, &output_min)); in Compute()
91 output_min->flat<float>()(0) = min_input; in Compute()
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| D | quantized_pooling_ops.cc | 94 Tensor* output_min = nullptr; in Compute() local
95 OP_REQUIRES_OK(context, context->allocate_output(1, {}, &output_min)); in Compute()
96 output_min->flat<float>()(0) = min_input; in Compute()
118 Tensor* output_min = nullptr; in Compute() local
119 OP_REQUIRES_OK(context, context->allocate_output(1, {}, &output_min)); in Compute()
120 output_min->flat<float>()(0) = min_input; in Compute()
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| D | mkl_requantize_ops_test.cc | 163 const float output_min = GetOutput(0)->flat<float>()(0); in TEST_F() local
165 EXPECT_NEAR(-14.8217, output_min, 0.002); in TEST_F()
224 const float output_min = GetOutput(0)->flat<float>()(0); in TEST_F() local
226 EXPECT_NEAR(-6.0, output_min, 0.002); // Values are aligned with clip_value. in TEST_F()
293 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
295 EXPECT_NEAR(range_op_output_min, output_min, 0.002); in TEST_F()
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| D | quantization_utils_test.cc | 35 float input_max, float output_min, float output_max, in TestRequantizeMany() argument
44 output_min, output_max)); in TestRequantizeMany()
55 input_max, output_min, output_max, in TestRequantizeMany()
59 *eigen_device, i_tensor, input_min, input_max, output_min, output_max, in TestRequantizeMany()
71 << ", input_max=" << input_max << ", output_min=" << output_min in TestRequantizeMany()
77 float output_min, float output_max, in TestRequantizeMany8To32Bit() argument
86 output_min, output_max)); in TestRequantizeMany8To32Bit()
96 input_max, output_min, output_max, in TestRequantizeMany8To32Bit()
107 << ", input_max=" << input_max << ", output_min=" << output_min in TestRequantizeMany8To32Bit()
232 const float output_min = ranges[range_index][2]; in TestRequantizeManyInNewRangeEigenVsNonEigen() local
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| D | quantized_activation_ops_test.cc | 62 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
65 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max); in TEST_F()
93 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
96 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max); in TEST_F()
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| D | quantized_reshape_op.cc | 36 Tensor* output_min = nullptr; in Compute() local
37 OP_REQUIRES_OK(ctx, ctx->allocate_output(1, TensorShape({}), &output_min)); in Compute()
38 output_min->flat<float>()(0) = input_min_float; in Compute()
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| D | mkl_quantize_op_test.cc | 123 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
125 EXPECT_NEAR(0.0f, output_min, 1e-5f); in TEST_F()
153 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
155 EXPECT_NEAR(0.0f, output_min, 1e-5f); in TEST_F()
183 const float output_min = GetOutput(1)->flat<float>()(0); in TEST_F() local
185 EXPECT_NEAR(-0.8f, output_min, 1e-5f); in TEST_F()
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| /external/XNNPACK/src/ |
| D | subgraph.c | 128 float output_min, in xnn_define_convolution_2d() argument
186 if (isnan(output_min)) { in xnn_define_convolution_2d()
198 if (output_min >= output_max) { in xnn_define_convolution_2d()
202 output_min, output_max); in xnn_define_convolution_2d()
253 node->activation.output_min = output_min; in xnn_define_convolution_2d()
280 float output_min, in xnn_define_depthwise_convolution_2d() argument
332 if (isnan(output_min)) { in xnn_define_depthwise_convolution_2d()
344 if (output_min >= output_max) { in xnn_define_depthwise_convolution_2d()
348 output_min, output_max); in xnn_define_depthwise_convolution_2d()
398 node->activation.output_min = output_min; in xnn_define_depthwise_convolution_2d()
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| D | global-average-pooling-nwc.c | 31 uint8_t output_min, in xnn_create_global_average_pooling_nwc_q8() argument
85 if (output_min >= output_max) { in xnn_create_global_average_pooling_nwc_q8()
89 output_min, output_max); in xnn_create_global_average_pooling_nwc_q8()
127 global_average_pooling_op->output_min = output_min; in xnn_create_global_average_pooling_nwc_q8()
147 float output_min, in xnn_create_global_average_pooling_nwc_f32() argument
185 if (isnan(output_min)) { in xnn_create_global_average_pooling_nwc_f32()
197 if (output_min >= output_max) { in xnn_create_global_average_pooling_nwc_f32()
201 output_min, output_max); in xnn_create_global_average_pooling_nwc_f32()
224 …global_average_pooling_op->f32_avgpool_params = xnn_init_f32_avgpool_params(nanf(""), output_min, … in xnn_create_global_average_pooling_nwc_f32()
278 global_average_pooling_op->output_min, in xnn_setup_global_average_pooling_nwc_q8()
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| D | binary-elementwise-nd.c | 21 float output_min, in create_binary_elementwise_nd_f32() argument
37 if (isnan(output_min)) { in create_binary_elementwise_nd_f32()
49 if (output_min >= output_max) { in create_binary_elementwise_nd_f32()
52 output_min, output_max); in create_binary_elementwise_nd_f32()
64 binary_elementwise_op->f32_output_params = xnn_init_f32_output_params(output_min, output_max); in create_binary_elementwise_nd_f32()
80 float output_min, in xnn_create_add_nd_f32() argument
86 output_min, output_max, flags, xnn_operator_type_add_nd_f32, add_op_out); in xnn_create_add_nd_f32()
90 float output_min, in xnn_create_divide_nd_f32() argument
96 output_min, output_max, flags, xnn_operator_type_divide_nd_f32, divide_op_out); in xnn_create_divide_nd_f32()
118 float output_min, in xnn_create_multiply_nd_f32() argument
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| D | clamp-nc.c | 26 uint8_t output_min, in xnn_create_clamp_nc_u8() argument
63 if (output_min >= output_max) { in xnn_create_clamp_nc_u8()
66 output_min, output_max); in xnn_create_clamp_nc_u8()
81 clamp_op->u8_output_params = xnn_init_u8_output_params(output_min, output_max); in xnn_create_clamp_nc_u8()
100 float output_min, in xnn_create_clamp_nc_f32() argument
137 if (isnan(output_min)) { in xnn_create_clamp_nc_f32()
149 if (output_min >= output_max) { in xnn_create_clamp_nc_f32()
152 output_min, output_max); in xnn_create_clamp_nc_f32()
167 clamp_op->f32_output_params = xnn_init_f32_output_params(output_min, output_max); in xnn_create_clamp_nc_f32()
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| D | global-average-pooling-ncw.c | 22 float output_min, in xnn_create_global_average_pooling_ncw_f32() argument
44 if (isnan(output_min)) { in xnn_create_global_average_pooling_ncw_f32()
56 if (output_min >= output_max) { in xnn_create_global_average_pooling_ncw_f32()
60 output_min, output_max); in xnn_create_global_average_pooling_ncw_f32()
81 …ooling_op->f32_gavgpool_params = xnn_init_f32_gavgpool_params(nanf(""), output_min, output_max, 0); in xnn_create_global_average_pooling_ncw_f32()
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| D | fully-connected-nc.c | 39 uint8_t output_min, in xnn_create_fully_connected_nc_q8() argument
105 if (output_min >= output_max) { in xnn_create_fully_connected_nc_q8()
109 output_min, output_max); in xnn_create_fully_connected_nc_q8()
172 requantization_scale, output_zero_point, output_min, output_max); in xnn_create_fully_connected_nc_q8()
201 float output_min, in xnn_create_fully_connected_nc_f32() argument
246 if (isnan(output_min)) { in xnn_create_fully_connected_nc_f32()
258 if (output_min >= output_max) { in xnn_create_fully_connected_nc_f32()
261 output_min, output_max); in xnn_create_fully_connected_nc_f32()
307 fully_connected_op->f32_output_params = xnn_init_f32_output_params(output_min, output_max); in xnn_create_fully_connected_nc_f32()
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| D | max-pooling-nhwc.c | 52 uint8_t output_min, in xnn_create_max_pooling2d_nhwc_u8() argument
121 if (output_min >= output_max) { in xnn_create_max_pooling2d_nhwc_u8()
125 output_min, output_max); in xnn_create_max_pooling2d_nhwc_u8()
152 max_pooling_op->u8_output_params = xnn_init_u8_output_params(output_min, output_max); in xnn_create_max_pooling2d_nhwc_u8()
181 float output_min, in xnn_create_max_pooling2d_nhwc_f32() argument
251 if (isnan(output_min)) { in xnn_create_max_pooling2d_nhwc_f32()
263 if (output_min >= output_max) { in xnn_create_max_pooling2d_nhwc_f32()
266 output_min, output_max); in xnn_create_max_pooling2d_nhwc_f32()
293 max_pooling_op->f32_output_params = xnn_init_f32_output_params(output_min, output_max); in xnn_create_max_pooling2d_nhwc_f32()
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| /external/XNNPACK/include/ |
| D | xnnpack.h | 239 float output_min,
288 float output_min,
317 float output_min,
345 float output_min,
380 float output_min,
508 float output_min,
534 float output_min,
561 float output_min,
579 float output_min,
609 float output_min,
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| /external/XNNPACK/test/ |
| D | argmaxpool-microkernel-tester.h | 208 const float output_min = accumulated_min + float(qmin()) / 255.0f * accumulated_range; variable
215 output_params = xnn_init_f32_output_params(output_min, output_max);
218 output_params = xnn_init_scalar_f32_output_params(output_min, output_max);
224 output_value = std::max(std::min(output_value, output_max), output_min);
237 ASSERT_GE(output[x * output_stride() + c], output_min)
311 const float output_min = accumulated_min + float(qmin()) / 255.0f * accumulated_range; variable
318 output_params = xnn_init_f32_output_params(output_min, output_max);
321 output_params = xnn_init_scalar_f32_output_params(output_min, output_max);
327 output_value = std::max(std::min(output_value, output_max), output_min);
342 ASSERT_GE(output[x * output_stride() + c], output_min)
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