| /cmsis-nn-latest/Tests/UnitTest/RefactoredTestGen/Lib/ |
| D | op_conv.py | 25 def generate_data(tflite_fname, params): argument
37 if params["tflite_generator"] == "json":
41 model_path=str(tflite_fname), arena_size=params["arena_size"],
52 scales["scaling_factors"] = params["w_scale"]
59 if params["generate_bias"]:
69 if params["generate_bias"]:
84 if params["generate_bias"]:
89 def calculate_padding(x_output, y_output, params): argument
90 x_input = params["input_w"]
91 y_input = params["input_h"]
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| D | op_fully_connected.py | 44 def get_shapes(params): argument
48 params["batch_size"] = 1 if "batch_size" not in params else params["batch_size"]
49 params["generate_bias"] = True if "generate_bias" not in params else params["generate_bias"]
50 if "out_activation_min" not in params:
51 params["out_activation_min"] = Lib.op_utils.get_dtype_min(params["input_data_type"])
52 if "out_activation_max" not in params:
53 params["out_activation_max"] = Lib.op_utils.get_dtype_max(params["input_data_type"])
55 if params["weights_data_type"] == "int4_t":
67 if "bias_min" not in params:
68 params["bias_min"] = b_min
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| D | op_pooling.py | 28 def get_shapes(params): argument
30 …shapes["input_tensor"] = (params["batch_size"], params["input_h"], params["input_w"], params["inpu…
35 def generate_keras_model(shapes, params): argument
38 if params["op_type"] == 'avgpool':
40 keras.layers.AveragePooling2D(pool_size=(params["filter_h"], params["filter_w"]),
41 strides=(params["stride_h"], params["stride_w"]),
42 padding=params["pad"],
44 elif params["op_type"] == 'maxpool':
46 keras.layers.MaxPooling2D(pool_size=(params["filter_h"], params["filter_w"]),
47 strides=(params["stride_h"], params["stride_w"]),
[all …]
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| D | op_pad.py | 28 def get_shapes(params): argument
30 …shapes["input_tensor"] = (params["input_n"], params["input_h"], params["input_w"], params["input_c…
35 def generate_keras_model(shapes, params): argument
40 …if (params["pre_pad_n"] == params["post_pad_n"] == params["pre_pad_h"] == params["post_pad_h"] == …
41 …dd(keras.layers.ZeroPadding2D(padding=((params["pre_pad_w"], params["post_pad_w"]), (params["pre_p…
42 …elif (params["pre_pad_n"] == params["post_pad_n"] == params["pre_pad_c"] == params["post_pad_c"] =…
43 …dd(keras.layers.ZeroPadding2D(padding=((params["pre_pad_h"], params["post_pad_h"]), (params["pre_p…
49 def generate_data_tflite(tflite_fname, params): argument
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| D | op_maximum_minimum.py | 28 def get_shapes(params): argument
30 …shapes["input_tensor_1"] = (params["batch_1"], params["height_1"], params["width_1"], params["chan…
31 …shapes["input_tensor_2"] = (params["batch_2"], params["height_2"], params["width_2"], params["chan…
32 …shapes["representational_dataset"] = (params["batch_1"], params["height_1"], params["width_1"], pa…
33 …shapes["representational_dataset2"] = (params["batch_2"], params["height_2"], params["width_2"], p…
38 def generate_keras_model(shapes, params): argument
41 if params['layer_type'] == "minimum":
43 elif params['layer_type'] == "maximum":
46 … input_1_shape = (params["batch_1"], params["height_1"], params["width_1"], params["channel_1"])
47 … input_2_shape = (params["batch_2"], params["height_2"], params["width_2"], params["channel_2"])
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| D | op_batch_matmul.py | 28 def get_shapes(params): argument
30 …shapes["lhs_input_tensor"] = (params["lhs_batch"], params["lhs_height"], params["lhs_rows"], param…
31 …shapes["rhs_input_tensor"] = (params["rhs_batch"], params["rhs_height"], params["rhs_rows"], param…
32 …shapes["representational_dataset"] = (params["lhs_batch"], params["lhs_height"], params["lhs_rows"…
33 …shapes["representational_dataset2"] = (params["rhs_batch"], params["rhs_height"], params["rhs_rows…
38 def generate_keras_model(shapes, params): argument
40 …input_shape_lhs = (params["lhs_batch"], params["lhs_height"], params["lhs_rows"], params["lhs_cols…
41 …input_shape_rhs = (params["rhs_batch"], params["rhs_height"], params["rhs_rows"], params["rhs_cols…
45 … layer = tf.matmul(input_lhs, input_rhs, transpose_a=params["adj_x"], transpose_b=params["adj_y"])
50 def generate_data_tflite(tflite_fname, params): argument
[all …]
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| D | op_lstm.py | 28 def get_shapes(params): argument
30 if params["time_major"] and params["tflite_generator"] == "json":
31 … shapes["input_tensor"] = (params["time_steps"], params["batch_size"], params["input_size"])
33 … shapes["input_tensor"] = (params["batch_size"], params["time_steps"], params["input_size"])
35 shapes["input_weights"] = (params["input_size"], params["hidden_size"])
36 shapes["all_input_weights"] = (params["input_size"], params["hidden_size"] * 4)
38 shapes["hidden_weights"] = (params["hidden_size"], params["hidden_size"])
39 shapes["all_hidden_weights"] = (params["hidden_size"], params["hidden_size"] * 4)
41 shapes["bias"] = (1, params["hidden_size"])
42 shapes["all_bias"] = (params["hidden_size"] * 4, )
[all …]
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| D | op_transpose.py | 30 def get_shapes(params): argument
32 input_shape = copy.deepcopy(params["in_dim"])
38 def generate_keras_model(shapes, params): argument
41 layer = tf.transpose(input_lhs, perm=params["perm"])
46 def generate_data_tflite(tflite_fname, params): argument
53 input_shape = params["in_dim"]
54 perm = params["perm"]
64 params["in_dim"].append(0)
65 params["in_dim"].append(0)
69 params["in_dim"].append(0)
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| D | op_utils.py | 26 def __init__(self, params, tensors, scales, effective_scales, aliases={}): argument
27 … self.params = params # All other params which are generated rather than given in the test-plan
43 def generate_keras_model(output_path, shapes, params): argument
48 def generate_data_tflite(tflite_path, params) -> Generated_data: argument
56 def generate_data_json(shapes, params) -> Generated_data: argument
64 def post_model_update(tflite_path, generated_data, params) -> Generated_data: argument
79 def get_dtype(name, params): argument
81 return params["bias_data_type"]
83 if params["weights_data_type"] == "int4_t":
85 return params["weights_data_type"]
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| D | test.py | 54 def generate(params, args, fpaths): argument
58 if (params["interpreter"] == "tflite_runtime") and (not tflite_runtime_imported):
61 if (params["interpreter"] == "tflite_micro") and (not tflite_micro_imported):
65 op_type = get_op_type(params["op_type"])
66 shapes = op_type.get_shapes(params)
69 fpaths["data_folder"] = pathlib.Path("TestCases") / "TestData" / params["name"]
75 if params["tflite_generator"] == "keras":
76 keras_model = op_type.generate_keras_model(shapes, params)
80 per_tensor_quant_for_dense = not params["per_channel_quant"]
84 if "bias_data_type" in params:
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| D | test_suite.py | 21 def generate(params, args): argument
28 common_test_params = {key: val for key, val in params.items() if is_common(key)}
37 for test_params in params["tests"]:
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| /cmsis-nn-latest/Source/NNSupportFunctions/ |
| D | arm_nn_lstm_step_s16.c | 49 const cmsis_nn_lstm_params *params, in arm_nn_lstm_step_s16() argument
61 …arm_nn_lstm_calculate_gate_s16(data_in, hidden_in, ¶ms->forget_gate, params, forget_gate, batc… in arm_nn_lstm_step_s16()
70 params->forget_to_cell_multiplier, in arm_nn_lstm_step_s16()
71 params->forget_to_cell_shift, in arm_nn_lstm_step_s16()
74 params->hidden_size * params->batch_size); in arm_nn_lstm_step_s16()
76 …arm_nn_lstm_calculate_gate_s16(data_in, hidden_in, ¶ms->input_gate, params, input_gate, batch_… in arm_nn_lstm_step_s16()
78 …arm_nn_lstm_calculate_gate_s16(data_in, hidden_in, ¶ms->cell_gate, params, cell_gate, batch_of… in arm_nn_lstm_step_s16()
87 params->input_to_cell_multiplier, in arm_nn_lstm_step_s16()
88 params->input_to_cell_shift, in arm_nn_lstm_step_s16()
89 -params->cell_clip, in arm_nn_lstm_step_s16()
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| D | arm_nn_lstm_step_s8.c | 48 const cmsis_nn_lstm_params *params, in arm_nn_lstm_step_s8() argument
60 …arm_nn_lstm_calculate_gate_s8_s16(data_in, hidden_in, ¶ms->forget_gate, params, forget_gate, b… in arm_nn_lstm_step_s8()
69 params->forget_to_cell_multiplier, in arm_nn_lstm_step_s8()
70 params->forget_to_cell_shift, in arm_nn_lstm_step_s8()
73 params->hidden_size * params->batch_size); in arm_nn_lstm_step_s8()
75 …arm_nn_lstm_calculate_gate_s8_s16(data_in, hidden_in, ¶ms->input_gate, params, input_gate, bat… in arm_nn_lstm_step_s8()
76 …arm_nn_lstm_calculate_gate_s8_s16(data_in, hidden_in, ¶ms->cell_gate, params, cell_gate, batch… in arm_nn_lstm_step_s8()
85 params->input_to_cell_multiplier, in arm_nn_lstm_step_s8()
86 params->input_to_cell_shift, in arm_nn_lstm_step_s8()
87 -params->cell_clip, in arm_nn_lstm_step_s8()
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| D | arm_nn_lstm_calculate_gate_s16.c | 50 const cmsis_nn_lstm_params *params, in arm_nn_lstm_calculate_gate_s16() argument
55 memset(output, 0, params->hidden_size * params->batch_size * sizeof(int16_t)); in arm_nn_lstm_calculate_gate_s16()
63 params->input_size, in arm_nn_lstm_calculate_gate_s16()
64 params->hidden_size, in arm_nn_lstm_calculate_gate_s16()
65 params->batch_size, in arm_nn_lstm_calculate_gate_s16()
77 params->hidden_size, in arm_nn_lstm_calculate_gate_s16()
78 params->hidden_size, in arm_nn_lstm_calculate_gate_s16()
79 params->batch_size, in arm_nn_lstm_calculate_gate_s16()
83 …arm_nn_activation_s16(output, output, params->hidden_size * params->batch_size, 0, gate->activatio… in arm_nn_lstm_calculate_gate_s16()
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| D | arm_nn_lstm_calculate_gate_s8_s16.c | 57 const cmsis_nn_lstm_params *params, in arm_nn_lstm_calculate_gate_s8_s16() argument
62 memset(output, 0, params->hidden_size * params->batch_size * sizeof(int16_t)); in arm_nn_lstm_calculate_gate_s8_s16()
70 params->input_size, in arm_nn_lstm_calculate_gate_s8_s16()
71 params->hidden_size, in arm_nn_lstm_calculate_gate_s8_s16()
72 params->batch_size, in arm_nn_lstm_calculate_gate_s8_s16()
83 params->hidden_size, in arm_nn_lstm_calculate_gate_s8_s16()
84 params->hidden_size, in arm_nn_lstm_calculate_gate_s8_s16()
85 params->batch_size, in arm_nn_lstm_calculate_gate_s8_s16()
89 …arm_nn_activation_s16(output, output, params->hidden_size * params->batch_size, 0, gate->activatio… in arm_nn_lstm_calculate_gate_s8_s16()
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| /cmsis-nn-latest/Source/LSTMFunctions/ |
| D | arm_lstm_unidirectional_s16.c | 51 const cmsis_nn_lstm_params *params, in arm_lstm_unidirectional_s16() argument
56 memset(buffers->cell_state, 0, params->batch_size * params->hidden_size * sizeof(int16_t)); in arm_lstm_unidirectional_s16()
57 if (params->time_major) in arm_lstm_unidirectional_s16()
60 for (int t = 0; t < params->time_steps; t++) in arm_lstm_unidirectional_s16()
62 const int16_t *data_in = input + (t * params->batch_size * params->input_size); in arm_lstm_unidirectional_s16()
63 int16_t *hidden_out = output + (t * params->batch_size * params->hidden_size); in arm_lstm_unidirectional_s16()
64 …_cmsis_nn_status status = arm_nn_lstm_step_s16(data_in, hidden_in, hidden_out, params, buffers, 1); in arm_lstm_unidirectional_s16()
76 for (int t = 0; t < params->time_steps; t++) in arm_lstm_unidirectional_s16()
78 const int16_t *data_in = input + (t * params->input_size); in arm_lstm_unidirectional_s16()
79 int16_t *hidden_out = output + (t * params->hidden_size); in arm_lstm_unidirectional_s16()
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| D | arm_lstm_unidirectional_s8.c | 51 const cmsis_nn_lstm_params *params, in arm_lstm_unidirectional_s8() argument
56 memset(buffers->cell_state, 0, params->batch_size * params->hidden_size * sizeof(int16_t)); in arm_lstm_unidirectional_s8()
57 if (params->time_major) in arm_lstm_unidirectional_s8()
60 for (int t = 0; t < params->time_steps; t++) in arm_lstm_unidirectional_s8()
62 const int8_t *data_in = input + (t * params->batch_size * params->input_size); in arm_lstm_unidirectional_s8()
63 int8_t *hidden_out = output + (t * params->batch_size * params->hidden_size); in arm_lstm_unidirectional_s8()
64 …arm_cmsis_nn_status status = arm_nn_lstm_step_s8(data_in, hidden_in, hidden_out, params, buffers, … in arm_lstm_unidirectional_s8()
76 for (int t = 0; t < params->time_steps; t++) in arm_lstm_unidirectional_s8()
78 const int8_t *data_in = input + (t * params->input_size); in arm_lstm_unidirectional_s8()
79 int8_t *hidden_out = output + (t * params->hidden_size); in arm_lstm_unidirectional_s8()
[all …]
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| /cmsis-nn-latest/Tests/UnitTest/TestCases/test_arm_lstm_unidirectional_s16/ |
| D | test_arm_lstm_unidirectional_s16.c | 152 const cmsis_nn_lstm_params params = {LSTM_1_S16_TIME_MAJOR, in lstm_1_s16() local
177 …nn_status result = arm_lstm_unidirectional_s16(lstm_1_s16_input_tensor, output, ¶ms, &buffers); in lstm_1_s16()
298 const cmsis_nn_lstm_params params = {LSTM_2_S16_TIME_MAJOR, in lstm_2_s16() local
323 …nn_status result = arm_lstm_unidirectional_s16(lstm_2_s16_input_tensor, output, ¶ms, &buffers); in lstm_2_s16()
446 const cmsis_nn_lstm_params params = {LSTM_ONE_TIME_STEP_S16_TIME_MAJOR, in lstm_one_time_step_s16() local
472 arm_lstm_unidirectional_s16(lstm_one_time_step_s16_input_tensor, output, ¶ms, &buffers); in lstm_one_time_step_s16()
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| /cmsis-nn-latest/Tests/UnitTest/TestCases/test_arm_lstm_unidirectional_s8/ |
| D | test_arm_lstm_unidirectional_s8.c | 161 const cmsis_nn_lstm_params params = {LSTM_1_TIME_MAJOR, in lstm_1() local
186 …arm_cmsis_nn_status result = arm_lstm_unidirectional_s8(lstm_1_input_tensor, output, ¶ms, &buf… in lstm_1()
315 const cmsis_nn_lstm_params params = {LSTM_2_TIME_MAJOR, in lstm_2() local
340 …arm_cmsis_nn_status result = arm_lstm_unidirectional_s8(lstm_2_input_tensor, output, ¶ms, &buf… in lstm_2()
470 const cmsis_nn_lstm_params params = {LSTM_ONE_TIME_STEP_TIME_MAJOR, in lstm_one_time_step() local
495 …us result = arm_lstm_unidirectional_s8(lstm_one_time_step_input_tensor, output, ¶ms, &buffers); in lstm_one_time_step()
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| /cmsis-nn-latest/Include/ |
| D | arm_nnsupportfunctions.h | 1925 const cmsis_nn_lstm_params *params,
1949 const cmsis_nn_lstm_params *params,
1970 const cmsis_nn_lstm_params *params,
1991 const cmsis_nn_lstm_params *params,
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| D | arm_nnfunctions.h | 2780 const cmsis_nn_lstm_params *params,
2801 const cmsis_nn_lstm_params *params,
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| /cmsis-nn-latest/Documentation/Doxygen/style_template/ |
| D | extra_stylesheet.css | 1117 .params, .retval, .exception, .tparams {
1122 .params .paramname, .retval .paramname {
1127 .params .paramtype {
1132 .params .paramdir {
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