| /dports/misc/ncnn/ncnn-20211208/tests/ |
| H A D | test_lstm.cpp | 21 int num_directions = direction == 2 ? 2 : 1; in test_lstm() local
25 pd.set(1, outch * input_size * 4 * num_directions); in test_lstm()
30 weights[1] = RandomMat(outch * 4 * num_directions); in test_lstm()
45 int num_directions = direction == 2 ? 2 : 1; in test_lstm_layer_with_hidden() local
49 pd.set(1, outch * input_size * 4 * num_directions); in test_lstm_layer_with_hidden()
54 weights[1] = RandomMat(outch * 4 * num_directions); in test_lstm_layer_with_hidden()
61 ncnn::Mat cell = RandomMat(outch, num_directions); in test_lstm_layer_with_hidden()
80 int num_directions = direction == 2 ? 2 : 1; in test_lstm_layer_with_hidden_input() local
84 pd.set(1, outch * input_size * 4 * num_directions); in test_lstm_layer_with_hidden_input()
96 ncnn::Mat cell = RandomMat(outch, num_directions); in test_lstm_layer_with_hidden_input()
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| H A D | test_rnn.cpp | 21 int num_directions = direction == 2 ? 2 : 1; in test_rnn() local
25 pd.set(1, outch * input_size * num_directions); in test_rnn()
30 weights[1] = RandomMat(outch * num_directions); in test_rnn()
45 int num_directions = direction == 2 ? 2 : 1; in test_rnn_layer_with_hidden() local
49 pd.set(1, outch * input_size * num_directions); in test_rnn_layer_with_hidden()
54 weights[1] = RandomMat(outch * num_directions); in test_rnn_layer_with_hidden()
76 int num_directions = direction == 2 ? 2 : 1; in test_rnn_layer_with_hidden_input() local
80 pd.set(1, outch * input_size * num_directions); in test_rnn_layer_with_hidden_input()
85 weights[1] = RandomMat(outch * num_directions); in test_rnn_layer_with_hidden_input()
107 int num_directions = direction == 2 ? 2 : 1; in test_rnn_layer_with_hidden_output() local
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| H A D | test_gru.cpp | 21 int num_directions = direction == 2 ? 2 : 1; in test_gru() local
25 pd.set(1, outch * input_size * 3 * num_directions); in test_gru()
30 weights[1] = RandomMat(outch * 4 * num_directions); in test_gru()
45 int num_directions = direction == 2 ? 2 : 1; in test_gru_layer_with_hidden() local
49 pd.set(1, outch * input_size * 3 * num_directions); in test_gru_layer_with_hidden()
54 weights[1] = RandomMat(outch * 4 * num_directions); in test_gru_layer_with_hidden()
58 ncnn::Mat hidden = RandomMat(outch, num_directions); in test_gru_layer_with_hidden()
76 int num_directions = direction == 2 ? 2 : 1; in test_gru_layer_with_hidden_input() local
80 pd.set(1, outch * input_size * 3 * num_directions); in test_gru_layer_with_hidden_input()
85 weights[1] = RandomMat(outch * 4 * num_directions); in test_gru_layer_with_hidden_input()
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| /dports/astro/oskar/OSKAR-2.8.0/oskar/telescope/station/src/ |
| H A D | oskar_evaluate_pierce_points.c | 37 void oskar_evaluate_pierce_points_d(int num_directions, const double* hor_x,
51 int num_directions, in oskar_evaluate_pierce_points() argument
87 if ((int)oskar_mem_length(pierce_point_lat) < num_directions || in oskar_evaluate_pierce_points()
88 (int)oskar_mem_length(pierce_point_lon) < num_directions || in oskar_evaluate_pierce_points()
89 (int)oskar_mem_length(relative_path_length) < num_directions || in oskar_evaluate_pierce_points()
90 (int)oskar_mem_length(hor_x) < num_directions || in oskar_evaluate_pierce_points()
91 (int)oskar_mem_length(hor_y) < num_directions || in oskar_evaluate_pierce_points()
92 (int)oskar_mem_length(hor_z) < num_directions) in oskar_evaluate_pierce_points()
112 oskar_evaluate_pierce_points_d(num_directions, x_, y_, z_, in oskar_evaluate_pierce_points()
156 void oskar_evaluate_pierce_points_d(int num_directions, const double* hor_x, in oskar_evaluate_pierce_points_d() argument
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| /dports/astro/oskar/OSKAR-2.8.0/oskar/telescope/station/test/ |
| H A D | oskar_array_pattern_benchmark.cpp | 19 int benchmark(int num_elements, int num_directions, int num_element_types,
43 int num_directions = atoi(opt.get_arg(1)); in main() local
82 printf("- Number of directions: %i\n", num_directions); in main()
104 int status = benchmark(num_elements, num_directions, num_element_types, in main()
128 int benchmark(int num_elements, int num_directions, int num_element_types, in benchmark() argument
135 oskar_Mem *x = oskar_mem_create(precision, loc, num_directions, &status); in benchmark()
136 oskar_Mem *y = oskar_mem_create(precision, loc, num_directions, &status); in benchmark()
153 z = oskar_mem_create(precision, loc, num_directions, &status); in benchmark()
156 int num_signals = num_directions * num_elements; in benchmark()
158 beam = oskar_mem_create(type, loc, num_directions, &status); in benchmark()
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| /dports/misc/py-onnx/onnx-1.10.2/onnx/defs/rnn/ |
| H A D | defs.cc | 10 TensorShapeProto::Dimension num_directions, seq_length, batch_size, in RNNShapeInference() local
15 num_directions.set_dim_value(1); in RNNShapeInference()
17 num_directions.set_dim_value(2); in RNNShapeInference()
42 auto dims = {seq_length, num_directions, batch_size, hidden_size}; in RNNShapeInference()
45 auto dims = {batch_size, seq_length, num_directions, hidden_size}; in RNNShapeInference()
55 auto dims = {num_directions, batch_size, hidden_size}; in RNNShapeInference()
58 auto dims = {batch_size, num_directions, hidden_size}; in RNNShapeInference()
68 auto dims = {num_directions, batch_size, hidden_size}; in RNNShapeInference()
71 auto dims = {batch_size, num_directions, hidden_size}; in RNNShapeInference()
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| H A D | old.cc | 207 TensorShapeProto::Dimension num_directions, seq_length, batch_size, in RNNShapeInference1() local
212 num_directions.set_dim_value(1); in RNNShapeInference1()
214 num_directions.set_dim_value(2); in RNNShapeInference1()
247 ctx, 1, {num_directions, batch_size, hidden_size}); // Y_h in RNNShapeInference1()
250 ctx, 2, {num_directions, batch_size, hidden_size}); // Y_c in RNNShapeInference1()
722 TensorShapeProto::Dimension num_directions, seq_length, batch_size, in RNNShapeInference2() local
727 num_directions.set_dim_value(1); in RNNShapeInference2()
729 num_directions.set_dim_value(2); in RNNShapeInference2()
751 ctx, 0, {seq_length, num_directions, batch_size, hidden_size}); in RNNShapeInference2()
757 updateOutputShape(ctx, 1, {num_directions, batch_size, hidden_size}); in RNNShapeInference2()
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| /dports/misc/ncnn/ncnn-20211208/src/layer/ |
| H A D | rnn.cpp | 37 int num_directions = direction == 2 ? 2 : 1; in load_model() local
39 int size = weight_data_size / num_directions / num_output; in load_model()
42 weight_xc_data = mb.load(size, num_output, num_directions, 0); in load_model()
46 bias_c_data = mb.load(num_output, 1, num_directions, 0); in load_model()
50 weight_hc_data = mb.load(num_output, num_output, num_directions, 0); in load_model()
116 int num_directions = direction == 2 ? 2 : 1; in forward() local
124 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
175 int num_directions = direction == 2 ? 2 : 1; in forward() local
185 hidden.create(num_output, num_directions, 4u, hidden_allocator); in forward()
192 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| H A D | lstm.cpp | 37 int num_directions = direction == 2 ? 2 : 1; in load_model() local
39 int size = weight_data_size / num_directions / num_output / 4; in load_model()
42 weight_xc_data = mb.load(size, num_output * 4, num_directions, 0); in load_model()
46 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
50 weight_hc_data = mb.load(num_output, num_output * 4, num_directions, 0); in load_model()
170 int num_directions = direction == 2 ? 2 : 1; in forward() local
183 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
235 int num_directions = direction == 2 ? 2 : 1; in forward() local
247 hidden.create(num_output, num_directions, 4u, hidden_cell_allocator); in forward()
252 cell.create(num_output, num_directions, 4u, hidden_cell_allocator); in forward()
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| H A D | gru.cpp | 37 int num_directions = direction == 2 ? 2 : 1; in load_model() local
39 int size = weight_data_size / num_directions / num_output / 3; in load_model()
42 weight_xc_data = mb.load(size, num_output * 3, num_directions, 0); in load_model()
46 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
50 weight_hc_data = mb.load(num_output, num_output * 3, num_directions, 0); in load_model()
167 int num_directions = direction == 2 ? 2 : 1; in forward() local
175 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
226 int num_directions = direction == 2 ? 2 : 1; in forward() local
236 hidden.create(num_output, num_directions, 4u, hidden_allocator); in forward()
243 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| /dports/misc/glow/glow-f24d960e3cc80db95ac0bc17b1900dbf60ca044a/thirdparty/onnx/onnx/defs/rnn/ |
| H A D | defs.cc | 8 TensorShapeProto::Dimension num_directions, seq_length, batch_size, in RNNShapeInference() local
13 num_directions.set_dim_value(1); in RNNShapeInference()
15 num_directions.set_dim_value(2); in RNNShapeInference()
37 ctx, 0, {seq_length, num_directions, batch_size, hidden_size}); in RNNShapeInference()
43 updateOutputShape(ctx, 1, {num_directions, batch_size, hidden_size}); in RNNShapeInference()
49 updateOutputShape(ctx, 2, {num_directions, batch_size, hidden_size}); in RNNShapeInference()
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| H A D | old.cc | 203 TensorShapeProto::Dimension num_directions, seq_length, batch_size, in RNNShapeInference1() local
208 num_directions.set_dim_value(1); in RNNShapeInference1()
210 num_directions.set_dim_value(2); in RNNShapeInference1()
240 ctx, 0, {seq_length, num_directions, batch_size, hidden_size}); // Y in RNNShapeInference1()
243 ctx, 1, {num_directions, batch_size, hidden_size}); // Y_h in RNNShapeInference1()
246 ctx, 2, {num_directions, batch_size, hidden_size}); // Y_c in RNNShapeInference1()
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| /dports/misc/py-onnx-tf/onnx-tf-1.6.0/onnx_tf/handlers/backend/ |
| H A D | lstm.py | 24 num_directions = 2 if direction == "bidirectional" else 1
36 if num_directions == 2:
116 num_directions = 2 if direction == "bidirectional" else 1
136 tf_activations = [tf.nn.tanh] * num_directions
145 activation_idxs = [1, 4] if num_directions == 2 else [1]
158 is_bidirectional=num_directions == 2)):
174 if num_directions == 2:
179 if num_directions == 1:
181 elif num_directions == 2:
192 if num_directions == 1:
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| H A D | gru.py | 27 num_directions = 2 if direction == "bidirectional" else 1
38 if num_directions == 2:
108 num_directions = 2 if direction == "bidirectional" else 1
134 if num_directions == 2:
146 is_bidirectional=num_directions == 2)):
157 if num_directions == 2:
161 if num_directions == 1:
163 elif num_directions == 2:
174 if num_directions == 1:
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| H A D | rnn.py | 75 num_directions = 2 if direction == "bidirectional" else 1
100 if num_directions == 2:
112 is_bidirectional=num_directions == 2)):
121 if num_directions == 2:
125 if num_directions == 1:
127 elif num_directions == 2:
138 if num_directions == 1:
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| /dports/graphics/vapoursynth-waifu2x-ncnn-vulkan/vapoursynth-waifu2x-ncnn-vulkan-r4/deps/ncnn/src/layer/ |
| H A D | rnn.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output; in load_model()
44 weight_xc_data = mb.load(size, num_output, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 1, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output, num_directions, 0); in load_model()
118 int num_directions = direction == 2 ? 2 : 1; in forward() local
126 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| H A D | gru.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output / 3; in load_model()
44 weight_xc_data = mb.load(size, num_output * 3, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output * 3, num_directions, 0); in load_model()
169 int num_directions = direction == 2 ? 2 : 1; in forward() local
177 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| /dports/graphics/waifu2x-ncnn-vulkan/waifu2x-ncnn-vulkan-20210521/src/ncnn/src/layer/ |
| H A D | rnn.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output; in load_model()
44 weight_xc_data = mb.load(size, num_output, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 1, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output, num_directions, 0); in load_model()
118 int num_directions = direction == 2 ? 2 : 1; in forward() local
126 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| H A D | gru.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output / 3; in load_model()
44 weight_xc_data = mb.load(size, num_output * 3, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output * 3, num_directions, 0); in load_model()
169 int num_directions = direction == 2 ? 2 : 1; in forward() local
177 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| /dports/benchmarks/vkpeak/vkpeak-20210430/ncnn/src/layer/ |
| H A D | rnn.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output; in load_model()
44 weight_xc_data = mb.load(size, num_output, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 1, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output, num_directions, 0); in load_model()
118 int num_directions = direction == 2 ? 2 : 1; in forward() local
126 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| H A D | gru.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output / 3; in load_model()
44 weight_xc_data = mb.load(size, num_output * 3, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output * 3, num_directions, 0); in load_model()
169 int num_directions = direction == 2 ? 2 : 1; in forward() local
177 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| /dports/graphics/realsr-ncnn-vulkan/realsr-ncnn-vulkan-20210210/src/ncnn/src/layer/ |
| H A D | rnn.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output; in load_model()
44 weight_xc_data = mb.load(size, num_output, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 1, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output, num_directions, 0); in load_model()
118 int num_directions = direction == 2 ? 2 : 1; in forward() local
126 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| H A D | gru.cpp | 39 int num_directions = direction == 2 ? 2 : 1; in load_model() local
41 int size = weight_data_size / num_directions / num_output / 3; in load_model()
44 weight_xc_data = mb.load(size, num_output * 3, num_directions, 0); in load_model()
48 bias_c_data = mb.load(num_output, 4, num_directions, 0); in load_model()
52 weight_hc_data = mb.load(num_output, num_output * 3, num_directions, 0); in load_model()
169 int num_directions = direction == 2 ? 2 : 1; in forward() local
177 top_blob.create(num_output * num_directions, T, 4u, opt.blob_allocator); in forward()
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| /dports/games/solarus-quest-editor/solarus-quest-editor-e541e1312c242bff10aa1fb84a7eb8b6cb8504ba/resources/quest_converter/1_0_to_1_1/ |
| H A D | sprite_converter_1_0.lua | 20 local num_directions = 0
32 …animation.name, animation.src_image, num_directions, animation.frame_delay, animation.frame_to_loo…
35 num_directions = tonumber(num_directions)
39 or num_directions == nil
102 if #animation.directions == num_directions then
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| /dports/misc/ncnn/ncnn-20211208/src/layer/arm/ |
| H A D | lstm_arm.cpp | 57 int num_directions = direction == 2 ? 2 : 1; in create_pipeline() local
65 for (int dr = 0; dr < num_directions; dr++) in create_pipeline()
363 int num_directions = direction == 2 ? 2 : 1; in forward() local
445 int num_directions = direction == 2 ? 2 : 1; in forward() local
974 int num_directions = direction == 2 ? 2 : 1; in create_pipeline_fp16s() local
991 for (int dr = 0; dr < num_directions; dr++) in create_pipeline_fp16s()
1170 int num_directions = direction == 2 ? 2 : 1; in forward_fp16s() local
1235 int num_directions = direction == 2 ? 2 : 1; in forward_fp16s() local
1320 int num_directions = direction == 2 ? 2 : 1; in forward_fp16sa() local
1385 int num_directions = direction == 2 ? 2 : 1; in forward_fp16sa() local
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