| /external/eigen/unsupported/test/ |
| cxx11_tensor_scan.cpp | 23 Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive);
60 result = tensor.cumsum(0);
66 result = tensor.cumsum(1);
72 result = tensor.cumsum(2);
78 result = tensor.cumsum(3);
92 Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0);
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| /external/tensorflow/tensorflow/core/lib/histogram/ |
| histogram.cc | 132 double cumsum = cumsum_prev + buckets_[i]; local
134 // Find the first bucket whose cumsum >= threshold
135 if (cumsum >= threshold) {
136 // Prevent divide by 0 in remap which happens if cumsum == cumsum_prev
137 // This should only get hit when p == 0, cumsum == 0, and cumsum_prev == 0
138 if (cumsum == cumsum_prev) {
150 double weight = Remap(threshold, cumsum_prev, cumsum, lhs, rhs);
154 cumsum_prev = cumsum;
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| scan_ops_test.py | 57 if func == np.cumsum:
80 np_out = handle_options(np.cumsum, x, axis, exclusive, reverse)
82 tf_out = math_ops.cumsum(x, axis, exclusive, reverse).eval()
103 tf_out = math_ops.cumsum(x, axis).eval()
136 math_ops.cumsum(input_tensor, -3).eval()
140 math_ops.cumsum(input_tensor, 2).eval()
144 math_ops.cumsum(input_tensor, [0]).eval()
150 result = math_ops.cumsum(t, axis, exclusive, reverse)
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| weights_broadcast_test.py | 32 return np.reshape(np.cumsum(np.ones(shape), dtype=np.int32), newshape=shape)
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| functional_ops_test.py | 309 self.assertAllEqual(np.cumsum(elems), r_value[0])
310 self.assertAllEqual(np.cumsum(-elems), r_value[1])
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| /external/tensorflow/tensorflow/contrib/coder/python/ops/ |
| coder_ops_test.py | 39 cdf = math_ops.cumsum(histogram, exclusive=False)
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| /external/tensorflow/tensorflow/compiler/tests/ |
| scan_ops_test.py | 57 if func == np.cumsum:
80 np_out = handle_options(np.cumsum, x, axis, exclusive, reverse)
83 tf_out = math_ops.cumsum(p, axis, exclusive, reverse).eval(
106 math_ops.cumsum(p, axis).eval(feed_dict={p: x})
139 math_ops.cumsum(input_tensor, -3).eval()
143 math_ops.cumsum(input_tensor, 2).eval()
147 math_ops.cumsum(input_tensor, [0]).eval()
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| dask_io.py | 43 divisions = np.cumsum(lengths).tolist()
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| /external/tensorflow/tensorflow/contrib/sparsemax/python/ops/ |
| sparsemax.py | 58 z_cumsum = math_ops.cumsum(z_sorted, axis=1)
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| /external/tensorflow/tensorflow/contrib/layers/python/ops/ |
| sparse_ops.py | 159 # Use cumsum along the last dimension to generate per-row indexes.
166 math_ops.cumsum(binary_indicators, axis=-1), "row_index_indicators")
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| /external/bart/bart/sched/ |
| functions.py | 171 series = series.cumsum()
298 running = select_window(org_series.cumsum(), window)
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| /external/trappy/tests/ |
| test_stats.py | 274 return series.cumsum()
303 return series.cumsum()
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| test_plotter.py | 236 dfr = pd.DataFrame(data, columns=["tick", "tock"]).cumsum()
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| /external/eigen/bench/ |
| sparse_setter.cpp | 316 //cumsum the nnz per row to get Bp[]
317 for(int i = 0, cumsum = 0; i < n_row; i++){
319 Bp[i] = cumsum;
320 cumsum += temp;
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| /external/tensorflow/tensorflow/contrib/coder/kernels/ |
| range_coder_ops_test.cc | 201 histogram_tensor.flat_inner_dims<int32, 2>().cumsum(1);
423 cdf.flat<int32>() = h.cumsum(0);
463 cdf = h.cumsum(0);
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| mcmc_diagnostics_impl.py | 173 mask = math_ops.cumsum(mask, axis=0)
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| /external/tensorflow/tensorflow/contrib/image/python/kernel_tests/ |
| segmentation_test.py | 178 positive_id_start_per_image = np.cumsum(num_ids_per_image)
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| /external/tensorflow/tensorflow/contrib/sparsemax/python/kernel_tests/ |
| sparsemax_loss_test.py | 42 z_cumsum = np.cumsum(z_sorted, axis=1)
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| sparsemax_test.py | 42 z_cumsum = np.cumsum(z_sorted, axis=1)
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| /external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
| attention_wrapper.py | 583 """Computes cumprod of x in logspace using cumsum to avoid underflow.
588 exp(cumsum(log(x))). This function can be called identically to tf.cumprod.
592 *args: Passed on to cumsum; these are identical to those in cumprod.
593 **kwargs: Passed on to cumsum; these are identical to those in cumprod.
600 return math_ops.exp(math_ops.cumsum(
670 attention = p_choose_i*cumprod_1mp_choose_i*math_ops.cumsum(
676 p_choose_i *= math_ops.cumsum(previous_attention, axis=1)
[all...] |
| /external/tensorflow/tensorflow/contrib/metrics/python/ops/ |
| metric_ops.py | [all...] |
| /external/fio/tools/hist/ |
| fiologparser_hist.py | 38 cdf = 100 * (ws.cumsum() - ws / 2.0) / ws.sum()
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| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| periodic.py | 535 math_ops.cumsum(powers_above_zero), [(1, 0), (0, 0), (0, 0)])
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| /external/toolchain-utils/cros_utils/ |
| stats.py | 148 cumsum
218 ## arguments in-place ... cumsum, ranksort, ...
323 cumhist = cumsum(hist) # make cumulative histogram
485 cumhist = cumsum(copy.deepcopy(h))
503 cumhist = cumsum(copy.deepcopy(h))
561 cumhist = cumsum(copy.deepcopy(h))
1991 cumsum = Dispatch((lcumsum, (ListType, TupleType)),) variable
4499 cumsum = Dispatch((lcumsum, (ListType, TupleType)), (acumsum, (N.ndarray,))) variable
[all...] |
| /external/tensorflow/tensorflow/contrib/model_pruning/python/ |
| pruning.py | 505 cdf = math_ops.cumsum(histogram)
|
