| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| propagate_array_data_types.cc | 29 for (const auto& output : op->outputs) {
30 model->GetArray(output).data_type = data_type;
46 // Record data types of output before processing, so we can see at the
49 for (const auto& output : op->outputs) {
50 old_output_data_types[output] = model->GetArray(output).data_type;
52 // Do the actual output data types propagation.
70 // These operators produce an output with the same type as their 2nd input
86 // Output type of the Range op can be set via an attribute
104 auto output = op->outputs[i] local
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| /external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/core/ops/ |
| unpack_path_op.cc | 35 .Output("unpacked_path: float")
84 Tensor* output = nullptr; variable
89 OP_REQUIRES_OK(context, context->allocate_output(0, output_shape, &output));
91 tensorforest::Initialize(*output, 0.0f);
94 auto out = output->tensor<float, 2>();
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| /external/tensorflow/tensorflow/core/framework/ |
| log_memory.cc | 69 MemoryLogTensorOutput output; local
70 output.set_step_id(step_id);
71 output.set_kernel_name(kernel_name);
72 output.set_index(index);
73 tensor.FillDescription(output.mutable_tensor());
74 OutputToLog(output);
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| numeric_op.h | 28 // One input and one output, both the same type.
38 // Two inputs and one output, all the same type.
48 // For operations where the input and output are the same shape.
57 // Output shape is the same as input shape.
59 Tensor* output = nullptr; variable
61 {0}, 0, input.shape(), &output));
62 static_cast<CHILD*>(this)->Operate(context, input, output);
80 Tensor* output = nullptr; variable
82 {0, 1}, 0, a.shape(), &output));
88 static_cast<CHILD*>(this)->template Operate<NDIMS>(context, a, b, output); \
[all...] |
| /external/tensorflow/tensorflow/core/grappler/optimizers/ |
| loop_optimizer_test.cc | 53 GraphDef output; local
54 Status status = optimizer.Optimize(nullptr, item, &output);
57 VerifyGraphsEqual(item.graph, output, __FUNCTION__);
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| /external/tensorflow/tensorflow/core/kernels/ |
| bucketize_op.cc | 39 typename TTypes<int32, 1>::Tensor& output) {
44 output(i) = first_bigger_it - boundaries_vector.begin();
69 auto output = output_tensor->template flat<int32>(); variable
71 context, input, boundaries_, output));
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| cross_op.cc | 65 // Create the output Tensor with the same dimensions as the input Tensors.
66 Tensor* output = nullptr; variable
67 OP_REQUIRES_OK(context, context->allocate_output(0, in0.shape(), &output));
76 output->flat_inner_dims<Type>();
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| data_format_ops.cc | 53 Tensor* output = nullptr; variable
55 context->allocate_output(0, input.shape(), &output));
57 input.flat<T>(), output->flat<T>());
104 Tensor* output = nullptr; variable
106 context->allocate_output(0, input.shape(), &output));
108 context->eigen_device<Device>(), input.flat<T>(), output->flat<T>(),
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| encode_jpeg_op.cc | 122 Tensor* output = nullptr; variable
124 context->allocate_output(0, TensorShape({}), &output));
127 adjusted_flags, &output->scalar<string>()()),
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| encode_png_op.cc | 76 Tensor* output = nullptr; variable
78 context->allocate_output(0, TensorShape({}), &output));
84 &output->scalar<string>()(), nullptr),
91 compression_, &output->scalar<string>()(), nullptr),
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| fact_op.cc | 88 auto output = output_tensor->template scalar<string>(); local
92 output() = coded;
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| l2loss_op_gpu.cu.cc | 48 // The output is a single number.
49 Tensor* output = nullptr; variable
51 context->allocate_output(0, TensorShape({}), &output));
58 context, (T*)output->flat<T>().data(), input_itr, 1,
|
| mfcc_dct_test.cc | 31 std::vector<double> output; local
32 dct.Compute(input, &output);
38 ASSERT_EQ(output.size(), kCoefficientCount);
40 EXPECT_NEAR(output[i], expected[i], 1e-10);
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| parse_tensor_op.cc | 50 Tensor output; variable
52 proto, ctx->output_alloc_attr(0), &output));
55 ctx, out_type_ == output.dtype(),
57 DataTypeString(output.dtype()), ") and dtype (",
60 ctx->set_output(0, output);
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| quantized_activation_ops.cc | 37 Tensor* output = nullptr; variable
39 context->allocate_output(0, input.shape(), &output));
45 min_as_quantized, 255, output->flat<quint8>().data());
47 output->flat<T>().device(context->eigen_cpu_device()) =
70 Tensor* output = nullptr; variable
72 context->allocate_output(0, input.shape(), &output));
80 output->flat<quint8>().data());
82 output->flat<T>().device(context->eigen_cpu_device()) =
|
| quantized_pooling_ops.cc | 73 Tensor* output = nullptr; variable
75 0, params.forward_output_shape(), &output));
88 // Clamp the int32 output back into quantized space.
89 output->flat<T>() = int32_output.flat<int32>()
|
| random_shuffle_op.cc | 30 // TODO(irving): If performance is critical, generate output directly instead
73 // No shuffling is required, so copy input directly to output
90 Tensor* output = nullptr; variable
92 context->allocate_output(0, input.shape(), &output));
94 auto output_mat = output->flat_outer_dims<T>();
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| remote_fused_graph_execute_op.cc | 104 Tensor* output = nullptr; variable
109 [i, &ctx, &output](const TensorShape& shape) -> Tensor* {
110 TF_CHECK_OK(ctx->allocate_output(i, shape, &output));
111 return output;
115 // data type as output if no executor is used.
116 Tensor* output = nullptr; variable
118 TF_CHECK_OK(ctx->allocate_output(i, ts, &output));
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| requantize.cc | 47 Tensor* output = nullptr; variable
48 OP_REQUIRES_OK(ctx, ctx->allocate_output(0, input.shape(), &output));
68 auto output_array = output->flat<T2>();
83 output->flat<quint8>().data());
88 requested_output_max_float, output);
|
| sparse_slice_op.cc | 77 const sparse::SparseTensor output = variable
80 context->set_output(0, output.indices());
81 context->set_output(1, output.values());
83 const TensorShape output_shape(output.shape());
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| stateless_random_ops.cc | 47 // Allocate output
48 Tensor* output; variable
49 OP_REQUIRES_OK(context, context->allocate_output(0, shape, &output));
84 Fill(context, random::PhiloxRandom(counter, key), output);
89 Tensor* output) = 0;
98 Tensor* output) override {
100 auto flat = output->flat<T>();
|
| unravel_index_op.cc | 87 auto output = output_tensor->vec<Tidx>(); variable
89 output = output.constant(indices_tensor.scalar<Tidx>()());
90 output = output.binaryExpr(strides, mod_op<Tidx>()) / strides_shifted;
98 auto output = output_tensor->matrix<Tidx>(); variable
105 output = indices_tensor.vec<Tidx>()
108 output = output.binaryExpr(strides.reshape(reshape).broadcast(bcast),
|
| whole_file_read_ops.cc | 109 Tensor* output = nullptr; variable
111 TensorShape({}), &output));
114 &output->scalar<string>()()));
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| /external/tensorflow/tensorflow/core/lib/db/ |
| snapfn.cc | 121 auto output = local
123 if (output == nullptr) {
127 *output++ = static_cast<char>(type), --output_size;
128 snappy::RawCompress(data, static_cast<size_t>(size), output, &output_size);
129 sqlite3_result_blob(ctx, output - 1, static_cast<int>(output_size + 1),
184 auto output = local
186 if (output == nullptr) {
190 if (!snappy::RawUncompress(blob, static_cast<size_t>(size), output)) {
193 sqlite3_free(output);
197 sqlite3_result_text(ctx, output, static_cast<int>(output_size)
[all...] |
| /external/tensorflow/tensorflow/python/framework/ |
| test_ops.cc | 26 .Output("result: string")
31 .Output("result: string")
40 .Output("version: int32")
45 .Output("version: int32")
62 .Output("initialized: bool")
75 .Output("output1: float")
76 .Output("output2: string")
80 .Output("out: T")
94 Tensor* output; variable
96 ctx->allocate_output("result", TensorShape({}), &output));
136 Tensor* output = nullptr; variable
201 Tensor* output; variable
[all...] |
