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Results 1 - 8 of 8 for fft_length (0.24 sec)
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tensorflow/compiler/mlir/lite/transforms/legalize_patterns.td
(convertIntAttrTo32Bit $new_axis_mask), (convertIntAttrTo32Bit $shrink_axis_mask), (GetBoolAttr<false>))>; def LegalizeRfft2d : Pat< (TF_RFFT2DOp $input, $fft_length), (TFL_RFFT2dOp $input, $fft_length)>; def LegalizeComplexAbs : Pat<(TF_ComplexAbsOp $arg), (TFL_ComplexAbsOp $arg)>; def LegalizeReal : Pat<(TF_RealOp $arg), (TFL_RealOp $arg)>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 28.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
signal over the inner-most dimension of `input`. The inner-most dimension of `input` is assumed to be the result of `RFFT`: the `fft_length / 2 + 1` unique components of the DFT of a real-valued signal. If `fft_length` is not provided, it is computed from the size of the inner-most dimension of `input` (`fft_length = 2 * (inner - 1)`). If the FFT length used to compute `input` is odd, it should be provided since it cannot be inferred properly.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
Since the DFT of a real signal is Hermitian-symmetric, `RFFT2D` only returns the `fft_length / 2 + 1` unique components of the FFT for the inner-most dimension of `output`: the zero-frequency term, followed by the `fft_length / 2` positive-frequency terms. Along each axis `RFFT2D` is computed on, if `fft_length` is smaller than the corresponding dimension of `input`, the dimension is cropped. If it is larger,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK: "mhlo.fft"(%arg0) <{fft_length = dense<8> : tensor<1xi64>, fft_type = #mhlo<fft_type RFFT>}> : (tensor<8xf32> %0 = "tf.RFFT"(%arg0, %fftlength) : (tensor<8xf32>, tensor<1xi32>) -> tensor<5xcomplex<f32>> func.return %0 : tensor<5xcomplex<f32>> } // ----- // CHECK-LABEL: func @rfft_1D_padded func.func @rfft_1D_padded(%arg0: tensor<7xf32>) -> tensor<5xcomplex<f32>> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
return failure(); } int64_t fft_length; if (fft_length_attr.getNumElements() != 0) { fft_length = fft_length_attr.getValues<IntegerAttr>()[0].getInt(); } else { return failure(); } int64_t expected_dim = fft_length; std::string fft_string = "RFFT"; if (typeid(OpTy) == typeid(TF::IRFFTOp)) { expected_dim = fft_length / 2 + 1; fft_string = "IRFFT";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.td
let hasCanonicalizer = 1; } def TFR_GetLengthOp : TFR_Op<"get_length", [Pure]> { let description = [{ The `get_length` operation returns the number of tensors for a tfr.tensor_list. Example: ```mlir %2 = tfr.get_length(%1) : tfr.tensor -> index %2 = tfr.get_length %1 -> index ``` }]; let arguments = (ins TFR_TensorListType:$tensor_list);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 10:54:29 UTC 2024 - 17.4K bytes - Viewed (0) -
src/cmd/vendor/golang.org/x/sys/unix/bpxsvc_zos.go
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 16:12:58 UTC 2024 - 19.9K bytes - Viewed (0) -
RELEASE.md
* Add a bitwise module with bitwise_and, bitwise_or, bitwise_xor, and invert functions. * Add fixed-grid ODE integration routines. * Allow passing bounds to ScipyOptimizerInterface. * Correctness fixes for fft_length parameter to `tf.spectral.rfft` & `tf.spectral.irfft`. * Exported model signatures using the 'predict' method will no longer have their input and output keys silently ignored and rewritten to 'inputs' and
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)