| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| H A D | bidirectional_sequence_lstm.mod.py | 22 n_batch, argument
455 n_batch = 1 variable
464 n_batch=n_batch,
495 fw_activation_state_data=[0] * (n_batch * n_output),
497 fw_cell_state_data=[0] * (n_batch * n_cell),
498 bw_cell_state_data=[0] * (n_batch * n_cell),
503 n_batch = 1 variable
512 n_batch=n_batch,
518 input_data=[0] * (max_time * n_batch * n_fw_input),
545 fw_cell_state_data=[0] * (n_batch * n_cell),
[all …]
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| H A D | unidirectional_sequence_lstm_layer_norm_cifg_peephole_state_output.mod.py | 24 n_batch = 2 variable
31 "{%d, %d, %d}" % (max_time, n_batch, n_input))
71 "{%d, %d}" % (n_batch, n_output))
73 "{%d, %d}" % (n_batch, n_cell))
90 "{%d, %d, %d}" % (max_time, n_batch, n_output))
92 "{%d, %d}" % (n_batch, n_output))
94 "{%d, %d}" % (n_batch, n_cell))
181 golden_output[(max_time - 1) * (n_batch * n_output):],
189 input0[output_state_in] = [0 for _ in range(n_batch * n_output)]
190 input0[cell_state_in] = [0 for _ in range(n_batch * n_cell)]
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| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
| H A D | layer_norm_lstm.mod.py | 22 n_batch = 2 variable
69 "{%d, %d}" % (n_batch, n_output))
71 "{%d, %d}" % (n_batch, n_cell))
89 "{%d, %d}" % (n_batch, n_output))
91 "{%d, %d}" % (n_batch, n_cell))
183 scratch_buffer: [0] * (n_batch * n_cell * 4),
194 n_batch = 2 variable
241 "{%d, %d}" % (n_batch, n_output))
243 "{%d, %d}" % (n_batch, n_cell))
263 "{%d, %d}" % (n_batch, n_cell))
[all …]
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| H A D | lstm2_float16.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
138 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm2_state2_float16.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
133 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm3_float16.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
620 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ]
621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm3_state3_float16.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
644 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm_state2_float16.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
141 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm2_state_float16.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
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| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/ |
| H A D | lstm2.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
138 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm2_state2.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
133 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm3.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
620 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ]
621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm3_state3.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
644 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm_state2.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
141 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm2_state.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
132 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
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| H A D | lstm.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
140 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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| H A D | lstm3_state.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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| H A D | lstm3_state2.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
643 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
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| /aosp12/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
| H A D | lstm2_relaxed.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
133 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
139 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm2_state2_relaxed.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell * …
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
133 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 3) ],
134 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm_state2_relaxed.mod.py | 21 n_batch = 1 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
141 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
142 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| H A D | lstm3_relaxed.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
60 cell_state_out = Output("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
621 input0[cell_state_in] = [ 0 for _ in range(n_batch * n_cell) ]
622 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
[all …]
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| H A D | lstm3_state3_relaxed.mod.py | 21 n_batch = 2 variable
27 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
52 cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
58 scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell *…
59 output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_out…
60 cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
644 scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
645 cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
[all …]
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| /aosp12/packages/modules/NeuralNetworks/common/operations/ |
| H A D | LSTM.cpp | 348 const uint32_t n_batch = SizeOfDimension(input_, 0); in Prepare() local
376 outputShape->dimensions = {n_batch, n_output}; in Prepare()
381 outputStateShape->dimensions = {n_batch, n_output}; in Prepare()
386 cellStateShape->dimensions = {n_batch, n_cell}; in Prepare()
392 scratchShape->dimensions = {n_batch, n_cell * 3}; in Prepare()
395 scratchShape->dimensions = {n_batch, n_cell * 4}; in Prepare()
788 const uint32_t n_batch = input_shape.dimensions[0]; in LSTMStep() local
806 cell_scratch = input_gate_scratch + n_cell * n_batch; in LSTMStep()
829 std::fill_n(cell_scratch, n_cell * n_batch, 0.0f); in LSTMStep()
853 n_batch, input_gate_scratch); in LSTMStep()
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| /aosp12/packages/modules/NeuralNetworks/common/ |
| H A D | QuantUtils.cpp | 12 int n_batch, int n_input, int16_t* output) { in ApplyLayerNorm() argument
14 for (int i = 0; i < n_batch; ++i) { in ApplyLayerNorm()
87 for (int batch = 0; batch < n_batch; ++batch) { in ApplySigmoid()
101 for (int batch = 0; batch < n_batch; ++batch) { in CwiseMul()
113 int32_t n_batch, int32_t n_input, int32_t output_zp, int8_t* output) { in CwiseMul() argument
114 for (int batch = 0; batch < n_batch; ++batch) { in CwiseMul()
140 for (int batch = 0; batch < n_batch; ++batch) { in CwiseAdd()
151 for (int batch = 0; batch < n_batch; ++batch) { in CwiseClipping()
165 for (int batch = 0; batch < n_batch; ++batch) { in CwiseClipping()
179 const int16_t* batch_vector, int n_batch, in VectorBatchVectorCwiseProductAccumulate() argument
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