Searched refs:input_tensor (Results 1 - 25 of 154) sorted by relevance

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/external/tensorflow/tensorflow/contrib/gan/python/eval/python/
H A Deval_utils_impl.py34 def image_grid(input_tensor, grid_shape, image_shape=(32, 32), num_channels=3):
38 input_tensor: Tensor. Minibatch of images to format, either 4D
55 if grid_shape[0] * grid_shape[1] != int(input_tensor.shape[0]):
57 (grid_shape, int(input_tensor.shape[0])))
58 if len(input_tensor.shape) == 2:
60 if int(input_tensor.shape[1]) != num_features:
63 elif len(input_tensor.shape) == 4:
64 if (int(input_tensor.shape[1]) != image_shape[0] or
65 int(input_tensor.shape[2]) != image_shape[1] or
66 int(input_tensor
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/external/tensorflow/tensorflow/contrib/quantize/python/
H A Dinput_to_ops_test.py34 input_tensor = array_ops.zeros((1, 2, 3, 4))
37 consumer_operations = input_to_ops_map.ConsumerOperations(input_tensor.op)
44 input_tensor = array_ops.zeros((1, 2, 3, 4))
45 output_tensor = nn_ops.relu6(input_tensor)
48 consumer_operations = input_to_ops_map.ConsumerOperations(input_tensor.op)
55 input_tensor = array_ops.zeros((1, 2, 3, 4))
56 output_tensor_1 = nn_ops.relu6(input_tensor)
57 output_tensor_2 = input_tensor + output_tensor_1
58 output_tensor_3 = input_tensor * output_tensor_2
61 consumer_operations = input_to_ops_map.ConsumerOperations(input_tensor
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/external/tensorflow/tensorflow/core/kernels/
H A Dbitcast_op.cc42 const Tensor& input_tensor = context->input(0); variable
44 TensorShape adjusted_shape = input_tensor.shape();
47 (input_tensor.dims() > 0 &&
48 input_tensor.dim_size(input_tensor.dims() - 1) ==
50 input_tensor.dim_size(input_tensor.dims()) == -1,
54 input_tensor.shape().DebugString()));
59 adjusted_shape.RemoveDim(input_tensor.dims() - 1);
63 output_tensor.UnsafeCopyFromInternal(input_tensor, output_data_type
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H A Dguarantee_const_op.cc32 const Tensor& input_tensor = ctx->input(0); variable
34 if (!ctx->forward_input_to_output_with_shape(0, 0, input_tensor.shape(),
36 ctx->set_output(0, input_tensor);
H A Dnth_element_op.h29 void operator()(OpKernelContext* context, const Tensor& input_tensor,
H A Dstring_to_number_op.cc41 const Tensor* input_tensor; variable
42 OP_REQUIRES_OK(context, context->input("string_tensor", &input_tensor));
43 const auto& input_flat = input_tensor->flat<string>();
47 context->allocate_output("output", input_tensor->shape(),
H A Dbase64_ops.cc34 const Tensor& input_tensor = context->input(0); variable
36 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
39 auto input = input_tensor.flat<string>();
59 const Tensor& input_tensor = context->input(0); variable
61 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
64 auto input = input_tensor.flat<string>();
H A Dstring_to_hash_bucket_op.h37 const Tensor* input_tensor; variable
38 OP_REQUIRES_OK(context, context->input("input", &input_tensor));
39 const auto& input_flat = input_tensor->flat<string>();
43 context->allocate_output("output", input_tensor->shape(),
79 const Tensor* input_tensor; variable
80 OP_REQUIRES_OK(context, context->input("input", &input_tensor));
81 const auto& input_flat = input_tensor->flat<string>();
85 context->allocate_output("output", input_tensor->shape(),
H A Dstring_to_hash_bucket_op.cc34 const Tensor* input_tensor; variable
35 OP_REQUIRES_OK(context, context->input("string_tensor", &input_tensor));
36 const auto& input_flat = input_tensor->flat<string>();
40 context->allocate_output("output", input_tensor->shape(),
/external/tensorflow/tensorflow/contrib/periodic_resample/python/kernel_tests/
H A Dperiodic_resample_op_test.py34 input_tensor = numpy.arange(12).reshape((3, 4))
36 output_tensor = input_tensor.reshape((6, 2))
40 result = periodic_resample(input_tensor, desired_shape).eval()
45 input_tensor = numpy.arange(12).reshape((3, 4))
47 output_tensor = input_tensor.reshape((6, 2))[:-1]
51 result = periodic_resample(input_tensor, desired_shape).eval()
56 input_tensor = numpy.arange(2 * 2 * 4).reshape((2, 2, 4))
62 # NOTE: output_tensor != input_tensor.reshape((4, 4, -1))
65 result = periodic_resample(input_tensor, desired_shape).eval()
66 # input_tensor[
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/external/tensorflow/tensorflow/python/ops/
H A Dspectral_ops.py47 def _infer_fft_length_for_rfft(input_tensor, fft_rank):
48 """Infers the `fft_length` argument for a `rank` RFFT from `input_tensor`."""
50 fft_shape = input_tensor.get_shape()[-fft_rank:]
54 return _array_ops.shape(input_tensor)[-fft_rank:]
60 def _infer_fft_length_for_irfft(input_tensor, fft_rank):
61 """Infers the `fft_length` argument for a `rank` IRFFT from `input_tensor`."""
63 fft_shape = input_tensor.get_shape()[-fft_rank:]
67 fft_length = _array_ops.unstack(_array_ops.shape(input_tensor)[-fft_rank:])
78 def _maybe_pad_for_rfft(input_tensor, fft_rank, fft_length, is_reverse=False):
79 """Pads `input_tensor` t
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/external/tensorflow/tensorflow/contrib/layers/python/ops/
H A Dbucketization_op.py23 def bucketize(input_tensor, boundaries, name=None):
24 """Bucketizes input_tensor by given boundaries.
29 input_tensor: A `Tensor` which will be bucketize.
35 each value in `input_tensor`.
41 input_tensor, boundaries=boundaries, name=name)
/external/tensorflow/tensorflow/core/kernels/fuzzing/
H A Didentity_fuzz.cc26 Tensor input_tensor(tensorflow::DT_INT8,
28 auto flat_tensor = input_tensor.flat<int8>();
33 Status s = RunOneInput(input_tensor);
H A Dparse_tensor_op_fuzz.cc34 Tensor input_tensor(tensorflow::DT_STRING, TensorShape({}));
35 input_tensor.scalar<string>()() =
38 RunOneInput(input_tensor).IgnoreError();
H A Dencode_jpeg_fuzz.cc49 Tensor input_tensor(tensorflow::DT_UINT8,
51 auto flat_tensor = input_tensor.flat<uint8>();
56 RunOneInput(input_tensor).IgnoreError();
H A Dstring_split_fuzz.cc33 Tensor input_tensor(tensorflow::DT_STRING, TensorShape({}));
48 input_tensor.scalar<string>()() = string(
53 RunTwoInputs(input_tensor, delimeter_tensor).IgnoreError();
H A Dfuzz_session.h65 // RunOneInput(input_tensor);
111 // the supplied input_tensor to the "input1" node, and discarding
113 Status RunOneInput(const Tensor& input_tensor) { argument
114 return session_->Run({{"input1", input_tensor}}, {}, {"output"}, nullptr);
145 Tensor input_tensor(tensorflow::DT_STRING, TensorShape({}));
146 input_tensor.scalar<string>()() =
149 RunOneInput(input_tensor).IgnoreError();
/external/tensorflow/tensorflow/examples/adding_an_op/
H A Dcuda_op_kernel.cc39 const Tensor& input_tensor = context->input(0); variable
40 auto input = input_tensor.flat<int32>();
44 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
H A Dzero_out_op_kernel_1.cc42 const Tensor& input_tensor = context->input(0); variable
43 auto input = input_tensor.flat<int32>();
47 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
/external/tensorflow/tensorflow/tools/ci_build/builds/user_ops/
H A Dcuda_op_kernel.cc39 const Tensor& input_tensor = context->input(0); variable
40 auto input = input_tensor.flat<int32>();
44 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
H A Dzero_out_op_kernel_1.cc42 const Tensor& input_tensor = context->input(0); variable
43 auto input = input_tensor.flat<int32>();
47 OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
/external/tensorflow/tensorflow/contrib/text/python/ops/
H A Dskip_gram_ops.py41 def skip_gram_sample(input_tensor,
58 rank-1 `input_tensor` as a token. The window size used for each token will be
63 For example, given `input_tensor = ["the", "quick", "brown", "fox", "jumps"]`,
76 The same process is repeated for each element of `input_tensor` and
80 If `vocab_freq_table` is specified, tokens in `input_tensor` that are not
91 input_tensor: A rank-1 `Tensor` from which to generate skip-gram candidates.
100 `input_tensor` from which to start generating skip-gram candidates.
102 elements in `input_tensor` to use in generating skip-gram candidates. -1
108 frequency counts. If specified, any token in `input_tensor` that is not
115 kept in `input_tensor`
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H A Dskip_gram_ops_test.py46 input_tensor = constant_op.constant(
49 input_tensor, min_skips=2, max_skips=2)
72 input_tensor = constant_op.constant(
75 input_tensor, min_skips=2, max_skips=2, emit_self_as_target=True)
103 input_tensor = constant_op.constant([b"the", b"quick", b"brown"])
107 input_tensor, min_skips=0, max_skips=0, emit_self_as_target=False)
114 input_tensor, min_skips=0, max_skips=0, emit_self_as_target=True)
126 input_tensor = constant_op.constant([b"the", b"quick", b"brown"])
128 input_tensor, min_skips=100, max_skips=100)
143 input_tensor
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/external/tensorflow/tensorflow/contrib/layers/python/layers/
H A Dfeature_column.py166 ["input_tensor",
180 ["input_tensor",
251 input_tensor,
258 def _deep_embedding_lookup_arguments(self, input_tensor):
266 def _wide_embedding_lookup_arguments(self, input_tensor):
272 def _to_dense_tensor(self, input_tensor):
414 def id_tensor(self, input_tensor):
415 """Returns the id tensor from the given transformed input_tensor."""
416 return input_tensor
419 def weight_tensor(self, input_tensor)
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/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/
H A Dscatter_add_ndim_op.cc34 Tensor input_tensor = context->mutable_input(0, false); variable
45 input_tensor.shape().dims() + 1,
60 if (!CheckTensorBounds(context, input_tensor)) return;
64 auto input = input_tensor.flat<float>();
75 for (int32 i = 0; i < input_tensor.shape().dims() - num_dims; ++i) {
76 num_data_per_index *= input_tensor.shape().dim_size(num_dims + i);
87 const int32 m = last_size / input_tensor.shape().dim_size(j);

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