| /external/tensorflow/tensorflow/python/ops/signal/ |
| D | fft_ops.py | 33 def _infer_fft_length_for_rfft(input_tensor, fft_rank): argument
36 fft_shape = input_tensor.get_shape()[-fft_rank:]
40 return _array_ops.shape(input_tensor)[-fft_rank:]
46 def _infer_fft_length_for_irfft(input_tensor, fft_rank): argument
49 fft_shape = input_tensor.get_shape()[-fft_rank:]
53 fft_length = _array_ops.unstack(_array_ops.shape(input_tensor)[-fft_rank:])
64 def _maybe_pad_for_rfft(input_tensor, fft_rank, fft_length, is_reverse=False): argument
98 input_fft_shape = _array_ops.shape(input_tensor)[-fft_rank:]
99 outer_dims = _math_ops.maximum(0, input_rank - fft_rank)
112 def _rfft_wrapper(fft_fn, fft_rank, default_name): argument
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | fft_ops.cc | 46 const int fft_rank = Rank(); in Compute() local
48 ctx, input_shape.dims() >= fft_rank, in Compute()
49 errors::InvalidArgument("Input must have rank of at least ", fft_rank, in Compute()
62 fft_length.shape().dim_size(0) == fft_rank, in Compute()
64 fft_rank, "]")); in Compute()
67 for (int i = 0; i < fft_rank; ++i) { in Compute()
72 bool inner_most = (i == fft_rank - 1); in Compute()
75 auto input_index = input_shape.dims() - fft_rank + i; in Compute()
88 output_shape.set_dim(output_shape.dims() - fft_rank + i, dim); in Compute()
91 for (int i = 0; i < fft_rank; ++i) { in Compute()
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| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| D | runtime_single_threaded_fft.cc | 27 int32 double_precision, int32 fft_rank, int64 input_batch, in __xla_cpu_runtime_EigenSingleThreadedFft() argument
31 static_cast<bool>(double_precision), fft_rank, in __xla_cpu_runtime_EigenSingleThreadedFft()
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| D | runtime_fft.cc | 31 int32 double_precision, int32 fft_rank, int64 input_batch, in __xla_cpu_runtime_EigenFft() argument
39 static_cast<bool>(double_precision), fft_rank, input_batch, fft_length0, in __xla_cpu_runtime_EigenFft()
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| D | runtime_fft.h | 26 tensorflow::int32 double_precision, tensorflow::int32 fft_rank,
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| D | runtime_single_threaded_fft.h | 26 tensorflow::int32 double_precision, tensorflow::int32 fft_rank,
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| D | runtime_fft_impl.h | 245 FftType fft_type, bool double_precision, int32 fft_rank, in EigenFftImpl() argument
248 switch (fft_rank) { in EigenFftImpl()
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| D | ir_emitter.cc | 1047 const int fft_rank = fft_length.size(); in HandleFft() local
1055 b_.getInt32(fft_rank), b_.getInt64(input_batch), in HandleFft()
1056 b_.getInt64(fft_rank > 0 ? fft_length[0] : 0), in HandleFft()
1057 b_.getInt64(fft_rank > 1 ? fft_length[1] : 0), in HandleFft()
1058 b_.getInt64(fft_rank > 2 ? fft_length[2] : 0)}, in HandleFft()
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| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| D | fft_thunk.cc | 146 const int64 fft_rank = fft_length_.size(); in ExecuteOnStream() local
147 CHECK_LE(fft_rank, 3); in ExecuteOnStream()
149 for (int i = 0; i < input_shape_.dimensions_size() - fft_rank; ++i) { in ExecuteOnStream()
160 for (int i = 0; i < fft_rank; ++i) { in ExecuteOnStream()
161 auto dim_offset = input_shape_.dimensions_size() - fft_rank + i; in ExecuteOnStream()
171 &stream, fft_rank, fft_length, input_embed, input_stride, in ExecuteOnStream()
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | hlo_evaluator.cc | 999 void Sweep(int64 fft_rank, FftType fft_type, in Sweep() argument
1042 for (int64 sweep_axis = fft_rank - 1; sweep_axis >= 0; sweep_axis--) { in Sweep()
1043 sweep(sweep_axis, fft_rank - 1, 0); in Sweep()
1048 for (int64 sweep_axis = 0; sweep_axis < fft_rank; sweep_axis++) { in Sweep()
1049 sweep(sweep_axis, fft_rank - 1, 0); in Sweep()
1089 const absl::Span<const int64> src_strides, int64 fft_rank, in GenerateIndices() argument
1092 CHECK_GE(dst_lengths.size(), fft_rank); in GenerateIndices()
1094 CHECK_GE(src_lengths.size(), fft_rank); in GenerateIndices()
1111 generate(fft_rank - 1, dst_start, src_start, true); in GenerateIndices()
1131 int64 fft_rank, FftType fft_type, int64 fft_size, in CopyDataFromInput() argument
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| D | shape_inference.cc | 1876 const int64 fft_rank = fft_length.size(); in InferFftShape() local
1877 if (fft_rank < 1 || fft_rank > 3) { in InferFftShape()
1878 return InvalidArgument("FFT only supports ranks 1-3; got %d.", fft_rank); in InferFftShape()
1881 if (x.dimensions_size() < fft_rank) { \ in InferFftShape()
1885 fft_rank, x.dimensions_size()); \ in InferFftShape()
1903 for (int i = 0; i < fft_rank; i++) { in InferFftShape()
1904 if (in.dimensions(in.dimensions_size() - fft_rank + i) != in InferFftShape()
1909 in.dimensions_size() - fft_rank + i, in InferFftShape()
1910 in.dimensions(in.dimensions_size() - fft_rank + i), in InferFftShape()
1917 if (fft_length[fft_rank - 1] != 0) { in InferFftShape()
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | fft_ops.cc | 43 int fft_rank) in GenericFftOp() argument
44 : XlaOpKernel(ctx), fft_type_(fft_type), fft_rank_(fft_rank) {} in GenericFftOp()
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