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/external/tensorflow/tensorflow/lite/kernels/internal/
Dresize_nearest_neighbor_test.cc32 const RuntimeShape& output_shape, in TestReferenceResizeNearestNeighbor() argument
40 output_size_data.data(), output_shape, output_data.data()); in TestReferenceResizeNearestNeighbor()
51 RuntimeShape output_shape = {1, 1, 1, 1}; in TEST() local
55 output_shape, output_data); in TEST()
62 RuntimeShape output_shape = {1, 3, 3, 1}; in TEST() local
66 output_shape, output_data); in TEST()
73 RuntimeShape output_shape = {1, 2, 2, 1}; in TEST() local
77 output_shape, output_data); in TEST()
84 RuntimeShape output_shape = {1, 2, 5, 1}; in TEST() local
88 output_shape, output_data); in TEST()
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Ddepthwiseconv_quantized_test.cc110 const RuntimeShape& output_shape, uint8* output_data) { in DispatchDepthwiseConv() argument
130 pad_height, depth_multiplier, output_shape, output_shift); in DispatchDepthwiseConv()
136 << " output_width = " << output_shape.Dims(2) in DispatchDepthwiseConv()
137 << " output_height = " << output_shape.Dims(1); in DispatchDepthwiseConv()
142 bias_shape, bias_data, output_shape, output_data); in DispatchDepthwiseConv()
166 bias_shape, bias_data, output_shape, output_data); in DispatchDepthwiseConv()
191 << " output_width = " << output_shape.Dims(2) in DispatchDepthwiseConv()
192 << " output_height = " << output_shape.Dims(1) in DispatchDepthwiseConv()
200 bias_shape, bias_data, output_shape, output_data); in DispatchDepthwiseConv()
217 bias_shape, bias_data, output_shape, output_data); in DispatchDepthwiseConv()
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/
Dreference_ops.h136 const float* bias_data, const RuntimeShape& output_shape, in Conv() argument
149 TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4); in Conv()
153 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in Conv()
155 const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3); in Conv()
163 const int output_height = output_shape.Dims(1); in Conv()
164 const int output_width = output_shape.Dims(2); in Conv()
196 output_data[Offset(output_shape, batch, out_y, out_x, out_channel)] = in Conv()
209 const int32* bias_data, const RuntimeShape& output_shape, in Conv() argument
232 TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4); in Conv()
233 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in Conv()
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Dfully_connected.h33 const float* bias_data, const RuntimeShape& output_shape, in FullyConnected() argument
42 const int output_dims_count = output_shape.DimensionsCount(); in FullyConnected()
44 const int batches = FlatSizeSkipDim(output_shape, output_dims_count - 1); in FullyConnected()
46 output_shape, output_dims_count - 1); in FullyConnected()
69 const int32* bias_data, const RuntimeShape& output_shape, in FullyConnected() argument
80 TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1); in FullyConnected()
88 const int output_dim_count = output_shape.DimensionsCount(); in FullyConnected()
90 const int batches = FlatSizeSkipDim(output_shape, output_dim_count - 1); in FullyConnected()
92 output_shape, output_dim_count - 1); in FullyConnected()
118 const int32* bias_data, const RuntimeShape& output_shape, in FullyConnected() argument
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/external/tensorflow/tensorflow/lite/kernels/
Dsparse_to_dense.cc44 TfLiteStatus Resize(TfLiteContext* context, const TfLiteTensor* output_shape, in Resize() argument
46 const int output_dimensions = NumElements(output_shape); in Resize()
49 output_shape_array->data[i] = GetTensorData<T>(output_shape)[i]; in Resize()
57 const TfLiteTensor* output_shape, in CheckDimensionsMatch() argument
65 TF_LITE_ENSURE_EQ(context, NumElements(output_shape), 1); in CheckDimensionsMatch()
70 NumElements(output_shape)); in CheckDimensionsMatch()
133 const TfLiteTensor* output_shape, in ResizeOutputShape() argument
135 if (output_shape->type == kTfLiteInt32) { in ResizeOutputShape()
136 return Resize<int32_t>(context, output_shape, output); in ResizeOutputShape()
137 } else if (output_shape->type == kTfLiteInt64) { in ResizeOutputShape()
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Dreshape.cc32 TfLiteIntArray* output_shape) { in ResizeOutput() argument
44 for (int i = 0; i < output_shape->size; ++i) { in ResizeOutput()
45 int value = output_shape->data[i]; in ResizeOutput()
54 output_shape->data[stretch_dim] = num_input_elements / num_output_elements; in ResizeOutput()
55 num_output_elements *= output_shape->data[stretch_dim]; in ResizeOutput()
59 return context->ResizeTensor(context, output, output_shape); in ResizeOutput()
66 TfLiteIntArray* output_shape = TfLiteIntArrayCreate(shape->dims->data[0]); in GetOutputShapeFromTensor() local
67 for (int i = 0; i < output_shape->size; ++i) { in GetOutputShapeFromTensor()
68 output_shape->data[i] = shape->data.i32[i]; in GetOutputShapeFromTensor()
71 return output_shape; in GetOutputShapeFromTensor()
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Dtranspose_conv.cc107 const TfLiteTensor* output_shape, in ResizeIm2ColTensor() argument
111 if (output_shape->type != kTfLiteInt32) { in ResizeIm2ColTensor()
113 output_shape->type); in ResizeIm2ColTensor()
116 TF_LITE_ENSURE_EQ(context, NumElements(output_shape), 4); in ResizeIm2ColTensor()
118 im2col_shape_array->data[0] = output_shape->data.i32[0]; in ResizeIm2ColTensor()
119 im2col_shape_array->data[1] = output_shape->data.i32[1]; in ResizeIm2ColTensor()
120 im2col_shape_array->data[2] = output_shape->data.i32[2]; in ResizeIm2ColTensor()
140 const TfLiteTensor* output_shape = in Prepare() local
150 TF_LITE_ENSURE_EQ(context, NumDimensions(output_shape), 1); in Prepare()
161 if (!IsConstantTensor(output_shape)) { in Prepare()
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Daudio_spectrogram_test.cc75 std::vector<int> output_shape = m.GetOutputShape(); in TEST() local
76 EXPECT_EQ(3, output_shape.size()); in TEST()
77 EXPECT_THAT(output_shape, ElementsAre(1, 1, 5)); in TEST()
91 std::vector<int> output_shape = m.GetOutputShape(); in TEST() local
92 EXPECT_EQ(3, output_shape.size()); in TEST()
93 EXPECT_THAT(output_shape, ElementsAre(1, 1, 5)); in TEST()
107 std::vector<int> output_shape = m.GetOutputShape(); in TEST() local
108 EXPECT_THAT(output_shape, ElementsAre(1, 2, 5)); in TEST()
/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/
Dordered.py83 def _inverse_event_shape(self, output_shape): argument
84 if output_shape.ndims is None or output_shape[-1] is None:
85 return output_shape
86 if output_shape[-1] <= 1:
87 raise ValueError("output_shape[-1] = %d <= 1" % output_shape[-1])
88 return tensor_shape.TensorShape([output_shape[-1]])
90 def _inverse_event_shape_tensor(self, output_shape): argument
93 output_shape[-1], 1, message="Need last dimension greater than 1.")
94 output_shape = control_flow_ops.with_dependencies(
95 [is_greater_one], output_shape)
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Dsoftmax_centered.py90 def _inverse_event_shape(self, output_shape): argument
91 if output_shape.ndims is None or output_shape[-1] is None:
92 return output_shape
93 if output_shape[-1] <= 1:
94 raise ValueError("output_shape[-1] = %d <= 1" % output_shape[-1])
95 return tensor_shape.TensorShape([output_shape[-1] - 1])
97 def _inverse_event_shape_tensor(self, output_shape): argument
101 output_shape[-1], 1, message="Need last dimension greater than 1.")
102 output_shape = control_flow_ops.with_dependencies(
103 [is_greater_one], output_shape)
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/external/tensorflow/tensorflow/core/kernels/
Dbroadcast_to_op.cc46 TensorShape output_shape; in Compute() local
48 ctx->op_kernel().MakeShape(shape_tensor, &output_shape)); in Compute()
51 if (output_shape == input_shape) { in Compute()
56 OP_REQUIRES(ctx, input_shape.dims() <= output_shape.dims(), in Compute()
60 output_shape.dims(), ").")); in Compute()
63 OP_REQUIRES_OK(ctx, ctx->allocate_output(0, output_shape, &output_tensor)); in Compute()
65 if (output_shape.num_elements() == 0) { in Compute()
77 BCast bcast(BCast::FromShape(input_shape), BCast::FromShape(output_shape), in Compute()
82 output_shape.DebugString())); in Compute()
84 functor::BroadcastTo<Device, T>()(device, ctx, *output_tensor, output_shape, in Compute()
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Ddeserialize_sparse_variant_op.cc61 const Tensor* output_shape; in Compute() local
66 &output_shape, &total_non_zeros)); in Compute()
69 output_shape->NumElements(), &output_indices, in Compute()
73 context->set_output(2, *output_shape); in Compute()
91 Tensor* output_shape; in Compute() local
109 &output_shape)); in Compute()
111 auto output_shape_vec = output_shape->vec<int64>(); in Compute()
136 output_shape->NumElements() - input_dims_to_stack == in Compute()
141 i, "] was: ", output_shape->NumElements() - input_dims_to_stack, in Compute()
155 const int output_rank = output_shape->NumElements(); in Compute()
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Drpc_op.cc76 TensorShape output_shape({}); in ComputeAsync() local
81 output_shape.dims() == 0 || in ComputeAsync()
82 output_shape.dim_size(0) == t.dim_size(0), in ComputeAsync()
84 "Input vector shapes don't match: ", output_shape.DebugString(), in ComputeAsync()
87 output_shape = t.shape(); in ComputeAsync()
93 ctx, ctx->allocate_output(0, output_shape, &response_t), done); in ComputeAsync()
101 ctx, ctx->allocate_output(1, output_shape, &status_code_t), done); in ComputeAsync()
103 ctx, ctx->allocate_output(2, output_shape, &status_message_t), done); in ComputeAsync()
112 int64 num_elements = output_shape.num_elements(); in ComputeAsync()
Dreshape_util.cc58 TensorShape output_shape; in Reshape() local
71 output_shape.AddDim(1); in Reshape()
77 output_shape.AddDim(size); in Reshape()
93 output_shape.set_dim(unknown_index, missing); in Reshape()
97 context, output_shape.num_elements() == dense_size, in Reshape()
100 output_shape.num_elements())); in Reshape()
103 if (input_shape == output_shape) { in Reshape()
121 output_strides[d] = output_strides[d + 1] * output_shape.dim_size(d + 1); in Reshape()
148 for (int j = 0; j < output_shape.dims(); ++j) { in Reshape()
149 output_shape_vec(j) = output_shape.dim_size(j); in Reshape()
/external/tensorflow/tensorflow/python/ops/
Dsplit_benchmark.py58 def _run_graph(self, device, output_shape, variable, num_outputs, axis): argument
75 input_shape = [output_shape[0] * num_outputs, output_shape[1]]
76 sizes = [output_shape[0] for _ in range(num_outputs)]
78 input_shape = [output_shape[0], output_shape[1] * num_outputs]
79 sizes = [output_shape[1] for _ in range(num_outputs)]
82 low=max(1, output_shape[axis] - 2),
83 high=output_shape[axis] + 2,
87 input_shape = [total_size, output_shape[1]]
89 input_shape = [output_shape[0], total_size]
/external/tensorflow/tensorflow/lite/kernels/internal/reference/integer_ops/
Dpooling.h26 const RuntimeShape& output_shape, int8* output_data) { in AveragePool() argument
30 TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4); in AveragePool()
31 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in AveragePool()
32 const int depth = MatchingDim(input_shape, 3, output_shape, 3); in AveragePool()
35 const int output_height = output_shape.Dims(1); in AveragePool()
36 const int output_width = output_shape.Dims(2); in AveragePool()
73 output_data[Offset(output_shape, batch, out_y, out_x, channel)] = in AveragePool()
82 const int8* input_data, const RuntimeShape& output_shape, in MaxPool() argument
91 TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4); in MaxPool()
92 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in MaxPool()
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/external/tensorflow/tensorflow/core/grappler/utils/
Dsymbolic_shapes_test.cc78 TensorShapeProto output_shape; in TEST_F() local
80 ShapeAfterBroadcast(MakeShape({1, 2}), MakeShape({1, 2}), &output_shape)); in TEST_F()
81 EXPECT_TRUE(ShapesSymbolicallyEqual(MakeShape({1, 2}), output_shape)); in TEST_F()
83 &output_shape)); in TEST_F()
84 EXPECT_TRUE(ShapesSymbolicallyEqual(MakeShape({-2, 2}), output_shape)); in TEST_F()
86 &output_shape)); in TEST_F()
87 EXPECT_TRUE(ShapesSymbolicallyEqual(MakeShape({-2, 32}), output_shape)); in TEST_F()
89 &output_shape)); in TEST_F()
90 EXPECT_TRUE(ShapesSymbolicallyEqual(MakeShape({-2, -2}), output_shape)); in TEST_F()
92 &output_shape)); in TEST_F()
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/external/tensorflow/tensorflow/python/keras/layers/
Dmerge.py70 output_shape = list(shape1[:-len(shape2)])
73 output_shape.append(None)
75 output_shape.append(j)
77 output_shape.append(i)
83 output_shape.append(i)
84 return tuple(output_shape)
103 output_shape = None
105 output_shape = input_shape[0][1:]
111 output_shape = self._compute_elemwise_op_output_shape(output_shape, shape)
187 output_shape = None
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Dcore.py410 def _fix_unknown_dimension(self, input_shape, output_shape): argument
430 output_shape = list(output_shape)
434 for index, dim in enumerate(output_shape):
447 output_shape[unknown] = original // known
450 return output_shape
455 output_shape = [input_shape[0]]
457 output_shape += tuple(s if s != -1 else None for s in self.target_shape)
459 output_shape = [input_shape[0]]
460 output_shape += self._fix_unknown_dimension(input_shape[1:],
462 return tensor_shape.TensorShape(output_shape)
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/external/tensorflow/tensorflow/python/ops/parallel_for/
Dgradients.py48 output_shape = array_ops.shape(output)
73 [output_shape, array_ops.shape(out)[1:]], axis=0)
107 output_shape = output.shape
108 if not output_shape[0].is_compatible_with(inp.shape[0]):
111 if output_shape.is_fully_defined():
112 batch_size = int(output_shape[0])
113 output_row_size = output_shape.num_elements() // batch_size
115 output_shape = array_ops.shape(output)
116 batch_size = output_shape[0]
141 new_shape = array_ops.concat([output_shape, inp_shape[1:]], axis=0)
/external/tensorflow/tensorflow/python/framework/
Dcommon_shapes.py229 output_shape = [batch_size, out_rows, out_cols, depth_out]
232 output_shape = [output_shape[0], output_shape[3], output_shape[1],
233 output_shape[2]]
234 return [tensor_shape.TensorShape(output_shape)]
416 output_shape = [batch_size, out_rows, out_cols, depth]
419 output_shape = [output_shape[0], output_shape[3], output_shape[1],
420 output_shape[2]]
421 return [tensor_shape.TensorShape(output_shape)]
487 output_shape = [batch_size, out_rows, out_cols, depth]
495 output_shape = [batch_size, in_rows, in_cols, depth // ksize_d]
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/external/tensorflow/tensorflow/lite/kernels/internal/optimized/
Doptimized_ops.h299 int accum_shift, const RuntimeShape& output_shape, in GEMVForLstmCell() argument
304 TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1); in GEMVForLstmCell()
305 const int output_dim_count = output_shape.DimensionsCount(); in GEMVForLstmCell()
307 TFLITE_DCHECK_EQ(FlatSizeSkipDim(output_shape, output_dim_count - 1), 1); in GEMVForLstmCell()
310 output_shape, output_dim_count - 1); in GEMVForLstmCell()
486 int32 accum_multiplier, int accum_shift, const RuntimeShape& output_shape, in GEMVForLstmCellWithSymmetricRange() argument
491 TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1); in GEMVForLstmCellWithSymmetricRange()
492 const int output_dim_count = output_shape.DimensionsCount(); in GEMVForLstmCellWithSymmetricRange()
494 TFLITE_DCHECK_EQ(FlatSizeSkipDim(output_shape, output_dim_count - 1), 1); in GEMVForLstmCellWithSymmetricRange()
497 output_shape, output_dim_count - 1); in GEMVForLstmCellWithSymmetricRange()
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/external/tensorflow/tensorflow/python/kernel_tests/
Dbroadcast_to_ops_test.py63 output_shape = [2] * output_dim
65 v_tf = array_ops.broadcast_to(constant_op.constant(x), output_shape)
66 v_np = np.broadcast_to(x, output_shape)
72 output_shape = [2, 5, 3]
75 v_tf = array_ops.broadcast_to(constant_op.constant(x), output_shape)
76 v_np = np.broadcast_to(x, output_shape)
82 output_shape = [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 15, 3, 2, 2, 2]
85 v_tf = array_ops.broadcast_to(constant_op.constant(x), output_shape)
86 v_np = np.broadcast_to(x, output_shape)
92 output_shape = [1, 1, 1, 2, 5, 3, 2, 2, 2, 3, 3, 3]
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Dconcat_op_test.py195 output_shape = [10, 9, 2]
196 grad_inp = np.random.rand(*output_shape).astype(dtype.as_numpy_dtype)
200 grad_inp.flatten(), shape=output_shape)
226 output_shape = [9, 10, 2]
227 grad_inp = np.random.rand(*output_shape).astype("f")
229 grad_inp.flatten(), shape=output_shape)
254 output_shape = [10, 2, 9]
255 grad_inp = np.random.rand(*output_shape).astype("f")
257 grad_inp.flatten(), shape=output_shape)
284 output_shape = input_shape
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/external/tensorflow/tensorflow/contrib/lite/kernels/internal/optimized/
Doptimized_ops.h421 int accum_shift, const RuntimeShape& output_shape, in GEMVForLstmCell() argument
426 TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1); in GEMVForLstmCell()
427 const int output_dim_count = output_shape.DimensionsCount(); in GEMVForLstmCell()
429 TFLITE_DCHECK_EQ(FlatSizeSkipDim(output_shape, output_dim_count - 1), 1); in GEMVForLstmCell()
432 output_shape, output_dim_count - 1); in GEMVForLstmCell()
608 int32 accum_multiplier, int accum_shift, const RuntimeShape& output_shape, in GEMVForLstmCellWithSymmetricRange() argument
613 TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1); in GEMVForLstmCellWithSymmetricRange()
614 const int output_dim_count = output_shape.DimensionsCount(); in GEMVForLstmCellWithSymmetricRange()
616 TFLITE_DCHECK_EQ(FlatSizeSkipDim(output_shape, output_dim_count - 1), 1); in GEMVForLstmCellWithSymmetricRange()
619 output_shape, output_dim_count - 1); in GEMVForLstmCellWithSymmetricRange()
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