1 files changed, 0 insertions, 112 deletions
diff --git a/tensorflow/core/kernels/spectrogram.h b/tensorflow/core/kernels/spectrogram.h
deleted file mode 100644
index 5476a0a961..0000000000
--- a/tensorflow/core/kernels/spectrogram.h
+++ /dev/null
@@ -1,112 +0,0 @@
-/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-// Class for generating spectrogram slices from a waveform.
-// Initialize() should be called before calls to other functions.  Once
-// Initialize() has been called and returned true, The Compute*() functions can
-// be called repeatedly with sequential input data (ie. the first element of the
-// next input vector directly follows the last element of the previous input
-// vector). Whenever enough audio samples are buffered to produce a
-// new frame, it will be placed in output. Output is cleared on each
-// call to Compute*(). This class is thread-unsafe, and should only be
-// called from one thread at a time.
-// With the default parameters, the output of this class should be very
-// close to the results of the following MATLAB code:
-// overlap_samples = window_length_samples - step_samples;
-// window = hann(window_length_samples, 'periodic');
-// S = abs(spectrogram(audio, window, overlap_samples)).^2;
-
-#ifndef THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_
-#define THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_
-
-#include <complex>
-#include <deque>
-#include <vector>
-
-#include "third_party/fft2d/fft.h"
-#include "tensorflow/core/framework/op_kernel.h"
-#include "tensorflow/core/framework/tensor.h"
-
-namespace tensorflow {
-
-class Spectrogram {
- public:
-  Spectrogram() : initialized_(false) {}
-  ~Spectrogram() {}
-
-  // Initializes the class with a given window length and step length
-  // (both in samples). Internally a Hann window is used as the window
-  // function. Returns true on success, after which calls to Process()
-  // are possible. window_length must be greater than 1 and step
-  // length must be greater than 0.
-  bool Initialize(int window_length, int step_length);
-
-  // Initialize with an explicit window instead of a length.
-  bool Initialize(const std::vector<double>& window, int step_length);
-
-  // Processes an arbitrary amount of audio data (contained in input)
-  // to yield complex spectrogram frames. After a successful call to
-  // Initialize(), Process() may be called repeatedly with new input data
-  // each time.  The audio input is buffered internally, and the output
-  // vector is populated with as many temporally-ordered spectral slices
-  // as it is possible to generate from the input.  The output is cleared
-  // on each call before the new frames (if any) are added.
-  //
-  // The template parameters can be float or double.
-  template <class InputSample, class OutputSample>
-  bool ComputeComplexSpectrogram(
-      const std::vector<InputSample>& input,
-      std::vector<std::vector<std::complex<OutputSample>>>* output);
-
-  // This function works as the one above, but returns the power
-  // (the L2 norm, or the squared magnitude) of each complex value.
-  template <class InputSample, class OutputSample>
-  bool ComputeSquaredMagnitudeSpectrogram(
-      const std::vector<InputSample>& input,
-      std::vector<std::vector<OutputSample>>* output);
-
-  // Return reference to the window function used internally.
-  const std::vector<double>& GetWindow() const { return window_; }
-
-  // Return the number of frequency channels in the spectrogram.
-  int output_frequency_channels() const { return output_frequency_channels_; }
-
- private:
-  template <class InputSample>
-  bool GetNextWindowOfSamples(const std::vector<InputSample>& input,
-                              int* input_start);
-  void ProcessCoreFFT();
-
-  int fft_length_;
-  int output_frequency_channels_;
-  int window_length_;
-  int step_length_;
-  bool initialized_;
-  int samples_to_next_step_;
-
-  std::vector<double> window_;
-  std::vector<double> fft_input_output_;
-  std::deque<double> input_queue_;
-
-  // Working data areas for the FFT routines.
-  std::vector<int> fft_integer_working_area_;
-  std::vector<double> fft_double_working_area_;
-
-  TF_DISALLOW_COPY_AND_ASSIGN(Spectrogram);
-};
-
-}  // namespace tensorflow
-
-#endif  // THIRD_PARTY_TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_