| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_Cumsum.pbtxt | 21 If `True`, perform exclusive cumsum.
32 By default, this op performs an inclusive cumsum, which means that the first
36 tf.cumsum([a, b, c]) # => [a, a + b, a + b + c]
39 By setting the `exclusive` kwarg to `True`, an exclusive cumsum is
43 tf.cumsum([a, b, c], exclusive=True) # => [0, a, a + b]
46 By setting the `reverse` kwarg to `True`, the cumsum is performed in the
50 tf.cumsum([a, b, c], reverse=True) # => [a + b + c, b + c, c]
58 tf.cumsum([a, b, c], exclusive=True, reverse=True) # => [b + c, c, 0]
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| /external/eigen/unsupported/test/ |
| D | cxx11_tensor_scan.cpp | 23 Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive); in test_1d_scan()
60 result = tensor.cumsum(0); in test_4d_scan()
66 result = tensor.cumsum(1); in test_4d_scan()
72 result = tensor.cumsum(2); in test_4d_scan()
78 result = tensor.cumsum(3); in test_4d_scan()
92 Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0); in test_tensor_maps()
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| D | cxx11_tensor_scan_cuda.cu | 54 gpu_t_result.device(gpu_device) = gpu_t_input.cumsum(1); in test_cuda_cumsum()
55 t_result = t_input.cumsum(1); in test_cuda_cumsum()
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | 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/python/kernel_tests/ |
| D | scan_ops_test.py | 58 if func == np.cumsum:
81 np_out = handle_options(np.cumsum, x, axis, exclusive, reverse)
83 tf_out = math_ops.cumsum(x, axis, exclusive, reverse).eval()
106 tf_out = math_ops.cumsum(x, axis).eval()
150 math_ops.cumsum(input_tensor, -3).eval()
154 math_ops.cumsum(input_tensor, 2).eval()
158 math_ops.cumsum(input_tensor, [0]).eval()
164 result = math_ops.cumsum(t, axis, exclusive, reverse)
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| D | array_ops_test.py | 1417 cdf = np.cumsum(
1437 cdf = np.cumsum(
1464 cdf = np.cumsum(
1484 cdf = np.cumsum(
1510 cdf = np.cumsum(
1532 cdf = np.cumsum(
1560 cdf = np.cumsum(
1582 cdf = np.cumsum(
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| D | weights_broadcast_test.py | 33 return np.reshape(np.cumsum(np.ones(shape), dtype=np.int32), newshape=shape)
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| /external/tensorflow/tensorflow/core/lib/histogram/ |
| D | histogram.cc | 132 double cumsum = cumsum_prev + buckets_[i]; in Percentile() local
135 if (cumsum >= threshold) { in Percentile()
138 if (cumsum == cumsum_prev) { in Percentile()
150 double weight = Remap(threshold, cumsum_prev, cumsum, lhs, rhs); in Percentile()
154 cumsum_prev = cumsum; in Percentile()
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| /external/tensorflow/tensorflow/contrib/coder/python/ops/ |
| D | coder_ops_test.py | 39 cdf = math_ops.cumsum(histogram, exclusive=False)
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| /external/eigen/bench/ |
| D | sparse_setter.cpp | 317 for(int i = 0, cumsum = 0; i < n_row; i++){ in coo_tocsr() local
319 Bp[i] = cumsum; in coo_tocsr()
320 cumsum += temp; in coo_tocsr()
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| D | dask_io.py | 50 divisions = np.cumsum(lengths).tolist()
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | segment_id_ops.py | 102 splits = array_ops.concat([[0], math_ops.cumsum(row_lengths)], axis=0)
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| D | ragged_tensor.py | 351 row_splits = array_ops.concat([[0], math_ops.cumsum(row_lengths)], axis=0)
439 row_limits = math_ops.cumsum(row_lengths)
1205 limits = math_ops.cumsum(lengths)
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| D | ragged_util.py | 237 return array_ops.concat([[0], math_ops.cumsum(lengths)], axis=-1)
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| /external/tensorflow/tensorflow/contrib/sparsemax/python/ops/ |
| D | sparsemax.py | 65 z_cumsum = math_ops.cumsum(z_sorted, axis=1)
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| /external/tensorflow/tensorflow/contrib/metrics/python/ops/ |
| D | metric_ops.py | 1096 array_ops.pad(math_ops.cumsum(counts), paddings=[[1, 0]]), dtypes.int32)
1101 math_ops.cumsum(
1113 math_ops.cumsum(
1127 array_ops.pad(math_ops.cumsum(ordered_weights), paddings=[[1, 0]]),
1311 cum_weight_totals_for_true = math_ops.cumsum(weight_totals_for_true,
1313 cum_weight_totals_for_false = math_ops.cumsum(weight_totals_for_false,
1677 tp = math_ops.cumsum(tp_buckets_v, reverse=True, name='tp')
1678 fp = math_ops.cumsum(fp_buckets_v, reverse=True, name='fp')
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | ordered.py | 109 return math_ops.cumsum(x, axis=-1)
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| /external/tensorflow/tensorflow/contrib/coder/kernels/ |
| D | range_coder_ops_test.cc | 200 histogram_tensor.flat_inner_dims<int32, 2>().cumsum(1); in BuildCdf()
422 cdf.flat<int32>() = h.cumsum(0); in CreateRangeEncodeFullBroadcastGraph()
462 cdf = h.cumsum(0); in CreateRangeDecodeFullBroadcastGraph()
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| /external/tensorflow/tensorflow/contrib/layers/python/ops/ |
| D | sparse_ops.py | 166 math_ops.cumsum(binary_indicators, axis=-1), "row_index_indicators")
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| /external/tensorflow/tensorflow/contrib/image/python/kernel_tests/ |
| D | segmentation_test.py | 178 positive_id_start_per_image = np.cumsum(num_ids_per_image)
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| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| D | classifier_metrics_impl.py | 1079 inds_r = array_ops.concat([zero, math_ops.cumsum(sizes_r)], 0)
1080 inds_g = array_ops.concat([zero, math_ops.cumsum(sizes_g)], 0)
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| D | classifier_metrics_test.py | 100 inds_r = np.r_[0, np.cumsum(sizes_r)]
107 inds_g = np.r_[0, np.cumsum(sizes_g)]
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| /external/toolchain-utils/cros_utils/ |
| D | stats.py | 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
2179 cumhist = N.cumsum(hist) # make cumulative histogram
2609 cumhist = cumsum(h * 1)
2626 cumhist = cumsum(h * 1)
2680 cumhist = cumsum(h * 1)
4499 cumsum = Dispatch((lcumsum, (ListType, TupleType)), (acumsum, (N.ndarray,))) variable
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| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| D | periodic.py | 535 math_ops.cumsum(powers_above_zero), [(1, 0), (0, 0), (0, 0)])
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| /external/tensorflow/tensorflow/contrib/sparsemax/python/kernel_tests/ |
| D | sparsemax_loss_test.py | 42 z_cumsum = np.cumsum(z_sorted, axis=1)
|