| /external/tensorflow/tensorflow/compiler/xla/client/ |
| padding.cc | 57 int64 window_stride = window_strides[i]; local
59 // output dimension := ceil(input_dimension / window_stride).
123 tensorflow::MathUtil::CeilOfRatio(input_dimension, window_stride);
125 std::max<int64>((output_dimension - 1) * window_stride +
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| padding_test.cc | 29 int64 window_stride, Padding padding) {
30 return MakePadding({input_dimension}, {window_dimension}, {window_stride},
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| /external/tensorflow/tensorflow/core/kernels/data/experimental/ |
| sliding_window_dataset_op.cc | 50 int64 window_stride = 0; variable
52 ctx, ParseScalarArgument<int64>(ctx, "window_stride", &window_stride));
54 ctx, window_stride > 0,
55 errors::InvalidArgument("window_stride must be greater than zero."));
56 if (window_size == window_shift && window_stride == 1) {
59 << " and window_stride is 1, use `batch` instead.";
61 *output = new Dataset(ctx, window_size, window_shift, window_stride, input);
68 int64 window_stride, const DatasetBase* input)
72 window_stride_(window_stride),
121 Node* window_stride = nullptr; variable
146 const int64 window_stride = dataset()->window_stride_; variable
[all...] |
| /external/tensorflow/tensorflow/contrib/data/python/ops/ |
| sliding.py | 30 def __init__(self, input_dataset, window_size, window_shift, window_stride):
34 window_size, dtype=dtypes.int64, name="window_stride")
36 window_stride, dtype=dtypes.int64, name="window_stride")
46 window_stride=self._window_stride,
59 "stride=window_stride).flat_map(lambda x: x.batch(window_size))` "
64 window_stride=1):
68 is `window_size`, the stride of the input elements is `window_stride`, and the
84 a.apply(sliding_window_batch(window_size=3, window_stride=2)) ==
97 window_stride: (Optional.) A `tf.int64` scalar `tf.Tensor`, representing th
[all...] |
| /external/tensorflow/tensorflow/contrib/data/python/kernel_tests/ |
| slide_dataset_op_test.py | 51 def testSlideDataset(self, count, window_size, window_shift, window_stride):
67 # _SlideDataset(window_size, window_shift, window_stride).
74 window_stride=window_stride_t)))
88 window_stride_t: window_stride
91 (window_size - 1) * window_stride + 1)) // window_shift + 1
97 component[(i * window_shift + j * window_stride) % 7]**2,
116 window_stride):
131 # RepeatDataset(count) -> _SlideDataset(window_size, stride, window_stride).
138 window_stride=window_stride_t)))
152 window_stride_t: window_stride
[all...] |
| /external/tensorflow/tensorflow/core/kernels/data/ |
| window_dataset_op.cc | 48 int64 window_stride = 0; variable
50 ParseScalarArgument<int64>(ctx, "stride", &window_stride));
52 ctx, window_stride > 0,
59 *output = new Dataset(ctx, input, window_size, window_shift, window_stride,
67 int64 window_shift, int64 window_stride, bool drop_remainder)
72 window_stride_(window_stride),
147 const int64 window_stride = dataset()->window_stride_; variable
158 size_t target_size = TargetBufferSize(window_size, window_stride);
183 int num_elements = 1 + (buffer_.size() - 1) / window_stride;
186 status.Update(buffer_[window_stride * i].status)
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| pooling.cc | 40 std::vector<int64> window_stride(num_spatial_dims);
48 window_stride[i] = stride[dim];
67 window_ksize, window_stride, Padding::kValid);
|
