| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantize_op_test.cc | 121 .Attr("T", DataTypeToEnum<qint8>::v()) in TEST_F()
134 test::FillValues<qint8>(&expected, {-127, 0, 1, 1, 2, 64, 127}); in TEST_F()
135 test::ExpectTensorEqual<qint8>(expected, *GetOutput(0)); in TEST_F()
151 .Attr("T", DataTypeToEnum<qint8>::v()) in TEST_F()
162 test::FillValues<qint8>(&expected, {-64, 0, 127}); in TEST_F()
163 test::ExpectTensorEqual<qint8>(expected, *GetOutput(0)); in TEST_F()
179 .Attr("T", DataTypeToEnum<qint8>::v()) in TEST_F()
192 test::FillValues<qint8>(&expected, {-126, 0, 1, 2, 4, 64, 127}); in TEST_F()
193 test::ExpectTensorEqual<qint8>(expected, *GetOutput(0)); in TEST_F()
209 .Attr("T", DataTypeToEnum<qint8>::v()) in TEST_F()
[all …]
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| D | dequantize_op_test.cc | 118 RunDequantizeMinCombinedTest<qint8>(0, 255.0f); in TEST_F()
141 RunDequantizeScaledTest<qint8>(-255.0f, 127.0f, 0, 0.0); in TEST_F()
144 RunDequantizeScaledTest<qint8>(-10.0f, 127.0f, -127, -127.0); in TEST_F()
147 RunDequantizeScaledTest<qint8>(-2.0f, 1.0f, -127, -2.0); in TEST_F()
150 RunDequantizeScaledTest<qint8>(-1.0f, 300.0f, 42, 99.212601); in TEST_F()
185 BM_DequantizeMinCombinedCpu<qint8>(iters); in BM_DequantizeMinCombinedCpuQint8()
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| D | save_op_test.cc | 90 AddInput<qint8>(TensorShape({3, 2}), in TEST_F()
91 [](int x) -> qint8 { return *reinterpret_cast<qint8*>(&x); }); in TEST_F()
95 return *reinterpret_cast<qint32*>(&x) * qint8(2); in TEST_F()
223 qint8 data[6]; in TEST_F()
226 EXPECT_EQ(*reinterpret_cast<qint8*>(&i), data[i]); in TEST_F()
244 EXPECT_EQ(*reinterpret_cast<qint32*>(&i) * qint8(2), data[i]); in TEST_F()
452 AddInput<qint8>(TensorShape({3, 2}), in TEST_F()
453 [](int x) -> qint8 { return *reinterpret_cast<qint8*>(&x); }); in TEST_F()
457 return *reinterpret_cast<qint32*>(&x) * qint8(2); in TEST_F()
530 qint8 data[6]; in TEST_F()
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| D | save_v2_op_test.cc | 89 AddInput<qint8>(TensorShape({3, 2}), in TEST_F()
90 [](int x) -> qint8 { return *reinterpret_cast<qint8*>(&x); }); in TEST_F()
94 return *reinterpret_cast<qint32*>(&x) * qint8(2); in TEST_F()
206 EXPECT_EQ(*reinterpret_cast<qint8*>(&i), val.template flat<qint8>()(i)); in TEST_F()
222 EXPECT_EQ(*reinterpret_cast<qint32*>(&i) * qint8(2), in TEST_F()
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| D | quantized_bias_add_op.cc | 102 .TypeConstraint<qint8>("T1")
103 .TypeConstraint<qint8>("T2")
105 QuantizedBiasAddOp<qint8, qint8, qint32>);
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| D | maxpooling_op.h | 43 struct SpatialMaxPooling<Device, qint8> {
44 void operator()(const Device& d, typename TTypes<qint8, 4>::Tensor output,
45 typename TTypes<qint8, 4>::ConstTensor input, int window_rows,
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| D | restore_v2_op_test.cc | 143 Tensor input_6 = MakeInput<qint8>( in RunTest()
145 [](int x) -> qint8 { return *reinterpret_cast<qint8*>(&x); }); in RunTest()
150 return *reinterpret_cast<qint32*>(&x) * qint8(2); in RunTest()
258 EXPECT_EQ(*reinterpret_cast<qint8*>(&i), output->flat<qint8>()(i)); in RunTest()
270 EXPECT_EQ(*reinterpret_cast<qint32*>(&i) * qint8(2), in RunTest()
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| D | restore_op_test.cc | 125 Tensor input_6 = MakeInput<qint8>(TensorShape({3, 2}), [](int x) -> qint8 { in TEST_F()
126 return *reinterpret_cast<qint8*>(&x); in TEST_F()
132 return *reinterpret_cast<qint32*>(&x) * qint8(2); in TEST_F()
248 EXPECT_EQ(*reinterpret_cast<qint8*>(&i), output->flat<qint8>()(i)); in TEST_F()
260 EXPECT_EQ(*reinterpret_cast<qint32*>(&i) * qint8(2), in TEST_F()
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| D | depthtospace_op.cc | 70 constexpr bool is_int8x4 = std::is_same<T, qint8>::value; in Compute()
191 Name("DepthToSpace").Device(DEVICE_GPU).TypeConstraint<qint8>("T"),
192 DepthToSpaceOp<GPUDevice, qint8>);
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| D | spacetodepth_op.cc | 70 constexpr bool is_int8x4 = std::is_same<T, qint8>::value; in Compute()
191 Name("SpaceToDepth").Device(DEVICE_GPU).TypeConstraint<qint8>("T"),
192 SpaceToDepthOp<GPUDevice, qint8>);
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| D | dequantize_op.cc | 134 Name("Dequantize").Device(DEVICE_CPU).TypeConstraint<qint8>("T"),
135 DequantizeOp<CPUDevice, qint8>);
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| D | quantize_op.cc | 242 Name("QuantizeV2").Device(DEVICE_CPU).TypeConstraint<qint8>("T"),
243 QuantizeV2Op<CPUDevice, qint8>);
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| D | concat_lib_cpu.cc | 72 REGISTER(qint8)
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| D | maxpooling_op.cc | 1073 constexpr bool is_int8x4 = std::is_same<T, qint8>::value; in Compute()
1397 Name("MaxPool").Device(DEVICE_GPU).TypeConstraint<qint8>("T"),
1398 MaxPoolingNoMaskOp<GPUDevice, qint8>);
1404 .TypeConstraint<qint8>("T"),
1405 MaxPoolingV2Op<GPUDevice, qint8>);
1411 .TypeConstraint<qint8>("T")
1413 MaxPoolingV2Op<GPUDevice, qint8>);
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| /external/tensorflow/tensorflow/python/ops/ |
| D | dequantize_op_test.py | 43 dtypes.qint8: np.int8,
69 self._testDequantizeOp(np.array([-128, 0, 127]), -1.0, 2.0, dtypes.qint8)
70 self._testDequantizeOp(np.array([-2, 4, -17]), -5.0, -3.0, dtypes.qint8)
71 self._testDequantizeOp(np.array([0, -4, 42, -108]), 5.0, 40.0, dtypes.qint8)
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| /external/tensorflow/tensorflow/core/framework/ |
| D | type_traits.h | 41 struct is_quantized<qint8> : true_type {};
80 class numeric_limits<tensorflow::qint8>
97 struct is_signed<tensorflow::qint8> : public is_signed<tensorflow::int8> {};
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| D | tensor_test.cc | 312 t.matrix<qint8>()(a, b) = qint8(a * b); in TEST()
315 TestCopies<qint8>(t); in TEST()
723 auto nchw_vect_c = t_nchw_vect_c.tensor<qint8, 5>(); in TEST()
911 Tensor t1 = test::AsTensor<qint8>({0, 1, 2, 3, 4, 5}, {2, 3}); in TEST()
913 t2.flat<qint8>() = t1.flat<qint8>() + qint8(-2); in TEST()
914 Tensor t3 = test::AsTensor<qint8>({-2, -1, 0, 1, 2, 3}, {2, 3}); in TEST()
915 test::ExpectTensorEqual<qint8>(t2, t3); in TEST()
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| D | register_types.h | 78 #define TF_CALL_qint8(m) m(::tensorflow::qint8)
109 #define TF_CALL_qint8(m) m(::tensorflow::qint8)
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| D | numeric_types.h | 37 typedef Eigen::QInt8 qint8; typedef
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| /external/tensorflow/tensorflow/python/framework/ |
| D | dtypes.py | 165 return self.base_dtype in [qint8, quint8, qint16, quint16, qint32]
361 qint8 = DType(types_pb2.DT_QINT8) variable
417 types_pb2.DT_QINT8: qint8,
545 (_np_qint8, qint8),
644 qint8, quint8, qint16, quint16, qint32, qint8_ref, quint8_ref, qint16_ref,
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| D | tensor_util.py | 101 dtypes.qint8.as_numpy_dtype:
167 dtypes.qint8.as_numpy_dtype: SlowAppendQIntArrayToTensorProto,
230 dtypes.int8, dtypes.int64, dtypes.qint8, dtypes.quint8, dtypes.qint16,
327 dtypes.qint8: [_FilterInt, _FilterTuple],
400 dtypes.qint8, dtypes.quint8, dtypes.qint16, dtypes.quint16,
589 dtypes.qint32, dtypes.quint8, dtypes.qint8, dtypes.qint16, dtypes.quint16,
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| /external/tensorflow/tensorflow/contrib/fused_conv/kernels/ |
| D | fused_conv2d_bias_activation_op.cc | 54 struct RawType<qint8> {
118 constexpr bool is_int8x4 = std::is_same<T, qint8>::value; in FusedConv2DBiasActivationOp()
320 constexpr bool is_int8x4 = std::is_same<T, qint8>::value; in launch()
650 .TypeConstraint<qint8>("T")
654 FusedConv2DBiasActivationOp<GPUDevice, qint8, float, float>);
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_QuantizeV2.pbtxt | 45 if T == qint8, out[i] -= (range(T) + 1) / 2.0
56 If the output type was qint8 ([-128, 127]), the operation will additionally
58 with the range of qint8.
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| D | api_def_Dequantize.pbtxt | 24 if T == qint8, in[i] += (range(T) + 1)/ 2.0
36 Note that if quantizedtype is qint8, the operation will additionally add
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| /external/tensorflow/tensorflow/contrib/fused_conv/python/ops/ |
| D | fused_conv2d_bias_activation_op_test.py | 655 NchwToNchwVectC(nn_ops.relu(logit)), -128, 127, dtypes.qint8)
818 dtype=dtypes.float32), -1.0, 1.0, dtypes.qint8)
828 dtype=dtypes.float32), -1.0, 1.0, dtypes.qint8)
841 dtype=dtypes.float32), -1.0, 1.0, dtypes.qint8)
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