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123

/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dbidirectional_sequence_lstm.mod.py26 n_output, argument
104 "{{{}, {}}}".format(n_cell, n_output))
107 "{{{}, {}}}".format(n_cell, n_output))
110 "{{{}, {}}}".format(n_cell, n_output))
113 "{{{}, {}}}".format(n_cell, n_output))
149 "{{{}, {}}}".format(n_cell, n_output))
152 "{{{}, {}}}".format(n_cell, n_output))
155 "{{{}, {}}}".format(n_cell, n_output))
158 "{{{}, {}}}".format(n_cell, n_output))
181 "{{{}, {}}}".format(n_batch, n_output))
[all …]
Dbidirectional_sequence_lstm_state_output.mod.py23 n_output = 4 variable
38 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
40 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
42 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
44 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
63 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
65 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
77 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
79 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
81 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dunidirectional_sequence_lstm_layer_norm_cifg_peephole_state_output.mod.py28 n_output = 3 variable
46 "{%d, %d}" % (n_cell, n_output))
48 "{%d, %d}" % (n_cell, n_output))
51 "{%d, %d}" % (n_cell, n_output))
67 "{%d,%d}" % (n_output, n_cell))
71 "{%d, %d}" % (n_batch, n_output))
90 "{%d, %d, %d}" % (max_time, n_batch, n_output))
92 "{%d, %d}" % (n_batch, n_output))
181 golden_output[(max_time - 1) * (n_batch * n_output):],
189 input0[output_state_in] = [0 for _ in range(n_batch * n_output)]
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Dlayer_norm_lstm.mod.py25 n_output = 3 variable
40 "{%d, %d}" % (n_cell, n_output))
43 "{%d, %d}" % (n_cell, n_output))
45 "{%d, %d}" % (n_cell, n_output))
48 "{%d, %d}" % (n_cell, n_output))
65 "{%d,%d}" % (n_output, n_cell))
69 "{%d, %d}" % (n_batch, n_output))
89 "{%d, %d}" % (n_batch, n_output))
92 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
197 n_output = 3 variable
[all …]
Dquantized_lstm.mod.py23 n_output = n_cell variable
32 [n_output, n_input], weights_scale, weights_zero_point)
39 [n_output, n_output], weights_scale, weights_zero_point)
45 BiasType = ("TENSOR_INT32", [n_output], weights_scale / 128., 0)
52 OutputType = ("TENSOR_QUANT8_ASYMM", (n_batch, n_output), 1 / 128, 128)
110 n_output = n_cell variable
119 [n_output, n_input], weights_scale, weights_zero_point)
130 [n_output, n_output], weights_scale, weights_zero_point)
140 BiasType = ("TENSOR_INT32", [n_output], weights_scale / 128., 0)
151 OutputType = ("TENSOR_QUANT8_ASYMM", (n_batch, n_output), 1 / 128, 128)
Dbidirectional_sequence_lstm_float16_batch_major.mod.py23 n_output = 4 variable
38 "fw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
40 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
42 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
44 "fw_recurrent_to_output_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
63 "fw_projection_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_output, n_cell))
65 "fw_projection_bias", "TENSOR_FLOAT16", "{{{}}}".format(n_output))
77 "bw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
79 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
81 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm.mod.py23 n_output = 4 variable
38 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
40 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
42 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
44 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
63 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
65 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
77 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
79 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
81 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm_cifg_peephole.mod.py23 n_output = 4 variable
38 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
40 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
42 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
44 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
63 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
65 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
77 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
79 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
81 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dunidirectional_sequence_lstm_batch_major_peephole_projection_bias.mod.py28 n_output = 16 variable
43 "{%d, %d}" % (n_cell, n_output))
46 "{%d, %d}" % (n_cell, n_output))
48 "{%d, %d}" % (n_cell, n_output))
51 "{%d, %d}" % (n_cell, n_output))
68 "{%d,%d}" % (n_output, n_cell))
69 projection_bias = Input("projection_bias", "TENSOR_FLOAT32", "{%d}" % n_output)
72 "{%d, %d}" % (n_batch, n_output))
86 output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d}" % (n_batch, max_time, n_output))
702 input0[output_state_in] = [0 for _ in range(n_batch * n_output)]
Dlstm3_float16.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT16", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
Dlstm3_state3_float16.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT16", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
59 …t_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
645 output_state_out: [ 0 for x in range(n_batch * n_output) ],
Dbidirectional_sequence_lstm_norm_fw_output.mod.py24 n_output = 3 variable
39 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
41 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
43 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
45 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
64 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
66 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
78 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
80 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
82 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm_float16_batch_major_merge_outputs.mod.py24 n_output = 4 variable
39 "fw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
41 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
43 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
45 "fw_recurrent_to_output_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
64 "fw_projection_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_output, n_cell))
66 "fw_projection_bias", "TENSOR_FLOAT16", "{{{}}}".format(n_output))
78 "bw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
80 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
82 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm_merge_outputs.mod.py24 n_output = 4 variable
39 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
41 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
43 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
45 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
64 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
66 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
78 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
80 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
82 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm_aux_input.mod.py25 n_output = 4 variable
40 "fw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
42 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
44 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
46 "fw_recurrent_to_output_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
65 "fw_projection_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_output, n_cell))
67 "fw_projection_bias", "TENSOR_FLOAT32", "{{{}}}".format(n_output))
79 "bw_recurrent_to_input_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
81 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
83 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT32", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dbidirectional_sequence_lstm_float16_batch_major_aux_input.mod.py26 n_output = 4 variable
41 "fw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
43 "fw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
45 "fw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
47 "fw_recurrent_to_output_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
66 "fw_projection_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_output, n_cell))
68 "fw_projection_bias", "TENSOR_FLOAT16", "{{{}}}".format(n_output))
80 "bw_recurrent_to_input_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
82 "bw_recurrent_to_forget_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
84 "bw_recurrent_to_cell_weights", "TENSOR_FLOAT16", "{{{}, {}}}".format(n_cell, n_output))
[all …]
Dlstm3_state2_float16.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT16", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT16", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT16", "{%d, %d}" % (n_batch, n_output))
/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/
Dlstm3.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
621 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
Dlstm3_state3.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 …t_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
645 output_state_out: [ 0 for x in range(n_batch * n_output) ],
Dlstm2_state2.mod.py25 n_output = 4 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 …t_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
134 output_state_out: [ 0 for x in range(n_batch * n_output) ],
Dlstm3_state2.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
Dlstm3_state.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
/packages/modules/NeuralNetworks/common/cpu_operations/
DLSTMTest.cpp78 LSTMOpModel(uint32_t n_batch, uint32_t n_input, uint32_t n_cell, uint32_t n_output, in LSTMOpModel() argument
83 n_output_(n_output), in LSTMOpModel()
94 input_shapes.push_back({n_batch, n_output}); in LSTMOpModel()
118 {n_batch, n_output}, in LSTMOpModel()
120 {n_batch, n_output}, in LSTMOpModel()
138 OutputStateIn_.insert(OutputStateIn_.end(), n_batch * n_output, 0.f); in LSTMOpModel()
277 const int n_output = 4; in TEST() local
279 LSTMOpModel lstm(n_batch, n_input, n_cell, n_output, in TEST()
292 {n_cell, n_output}, // recurrent_to_input_weight tensor in TEST()
293 {n_cell, n_output}, // recurrent_to_forget_weight tensor in TEST()
[all …]
/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/
Dlstm3_relaxed.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 output_state_out = Output("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
622 input0[output_state_in] = [ 0 for _ in range(n_batch * n_output) ]
Dlstm3_state3_relaxed.mod.py25 n_output = 16 variable
34 …ut_weights = Input("recurrent_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
35 …t_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
36 …ell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
37 …t_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
48 projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
51 output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
59 …t_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
61 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
646 output_state_out: [ 0 for x in range(n_batch * n_output) ],

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