/AliOS-Things-master/components/ai_agent/src/engine/tflite-micro/tensorflow/lite/experimental/mlir/testing/op_tests/ |
A D | conv_bias_activation.py | 58 def get_tensor_shapes(parameters): argument 59 input_shape = parameters["input_shape"] 60 filter_size = parameters["filter_shape"] 73 strides=parameters["strides"], 74 dilations=parameters["dilations"], 84 def build_graph(parameters): argument 94 if parameters["data_format"] == "NCHW": 100 strides=parameters["strides"], 101 dilations=parameters["dilations"], 112 if parameters["data_format"] == "NCHW": [all …]
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A D | batchmatmul.py | 47 def build_graph(parameters): argument 49 placeholder0_shape = parameters["shapes"][0] 50 adj_a = parameters["adjoint_a"] 51 adj_b = parameters["adjoint_b"] 52 rhs_constant = parameters["rhs_constant"] 61 constant1_shape = parameters["shapes"][3] 73 placeholder1_shape = parameters["shapes"][1] 82 input0_shape = parameters["shapes"][2] 83 adj_a = parameters["adjoint_a"] 84 adj_b = parameters["adjoint_b"] [all …]
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A D | tensor_list_set_item.py | 40 def build_graph(parameters): argument 43 dtype=parameters["element_dtype"], 44 shape=[parameters["num_elements"]] + parameters["element_shape"]) 46 dtype=parameters["element_dtype"], shape=parameters["element_shape"]) 53 num_elements=parameters["num_elements"], 54 element_dtype=parameters["element_dtype"]) 57 def build_inputs(parameters, sess, inputs, outputs): argument 58 data = create_tensor_data(parameters["element_dtype"], 60 parameters["element_shape"]) 61 item = create_tensor_data(parameters["element_dtype"], [all …]
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A D | conv3d.py | 40 def build_graph(parameters): argument 43 dtype=parameters["input_dtype"], 45 shape=parameters["input_shape"]) 47 dtype=parameters["input_dtype"], 49 shape=parameters["filter_shape"]) 54 strides=parameters["strides"], 56 padding=parameters["padding"]) 62 parameters["input_dtype"], 63 parameters["input_shape"], 67 parameters["input_dtype"], [all …]
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A D | identify_dilated_conv.py | 44 def get_tensor_shapes(parameters): argument 45 input_shape = parameters["input_shape"] 46 filter_size = parameters["filter_shape"] 52 def build_graph(parameters): argument 60 if parameters["constant_filter"]: 74 strides=parameters["strides"], 75 dilations=parameters["dilations"], 76 padding=parameters["padding"], 77 data_format=parameters["data_format"]) 80 def build_inputs(parameters, sess, inputs, outputs): argument [all …]
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A D | tensor_list_concat.py | 39 def build_graph(parameters): argument 42 dtype=parameters["element_dtype"], 43 shape=[parameters["num_elements"]] + parameters["element_shape"]) 45 parameters["element_shape"]) 46 out = list_ops.tensor_list_concat(tensor_list, parameters["element_dtype"], 47 parameters["element_shape"]) 50 def build_inputs(parameters, sess, inputs, outputs): argument 51 data = create_tensor_data(parameters["element_dtype"], 52 [parameters["num_elements"]] + 53 parameters["element_shape"])
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A D | tensor_list_get_item.py | 40 def build_graph(parameters): argument 43 dtype=parameters["element_dtype"], 44 shape=[parameters["num_elements"]] + parameters["element_shape"]) 46 parameters["element_shape"]) 47 out = list_ops.tensor_list_get_item(tensor_list, parameters["index"], 48 parameters["element_dtype"]) 51 def build_inputs(parameters, sess, inputs, outputs): argument 52 data = create_tensor_data(parameters["element_dtype"], 53 [parameters["num_elements"]] + 54 parameters["element_shape"])
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A D | tensor_list_resize.py | 40 def build_graph(parameters): argument 43 dtype=parameters["element_dtype"], 44 shape=[parameters["num_elements"]] + parameters["element_shape"]) 46 parameters["element_shape"]) 48 parameters["new_size"]) 50 tensor_list, element_dtype=parameters["element_dtype"]) 53 def build_inputs(parameters, sess, inputs, outputs): argument 54 data = create_tensor_data(parameters["element_dtype"], 55 [parameters["num_elements"]] + 56 parameters["element_shape"])
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A D | static_rnn_with_control_flow_v2.py | 44 def build_graph(parameters): argument 47 num_batches = parameters["num_batches"] 48 time_step_size = parameters["time_step_size"] 49 input_vec_size = parameters["input_vec_size"] 50 num_cells = parameters["num_cells"] 54 dtype=parameters["dtype"], 62 if parameters["use_sequence_length"]: 75 def build_inputs(parameters, sess, inputs, outputs): argument 88 num_batches = parameters["num_batches"] 89 time_step_size = parameters["time_step_size"] [all …]
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A D | dynamic_rnn.py | 43 def build_graph(parameters): argument 45 num_batches = parameters["num_batches"] 46 time_step_size = parameters["time_step_size"] 47 input_vec_size = parameters["input_vec_size"] 48 num_cells = parameters["num_cells"] 55 lstm_cell, input_tensor, dtype=parameters["dtype"]) 58 def build_inputs(parameters, sess, inputs, outputs): argument 62 num_batches = parameters["num_batches"] 63 time_step_size = parameters["time_step_size"] 64 input_vec_size = parameters["input_vec_size"] [all …]
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A D | tensor_list_dynamic_shape.py | 39 def build_graph(parameters): argument 42 dtype=parameters["element_dtype"], shape=parameters["element_shape"]) 45 num_elements=parameters["num_elements"], 46 element_dtype=parameters["element_dtype"]) 49 condition = lambda i, _: i < parameters["num_elements"] 54 tf.constant(value=1, dtype=parameters["element_dtype"])) 61 num_elements=parameters["num_elements"], 62 element_dtype=parameters["element_dtype"]) 65 def build_inputs(parameters, sess, inputs, outputs): argument 66 item = create_tensor_data(parameters["element_dtype"], [all …]
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A D | einsum.py | 49 def build_graph(parameters): argument 51 input0_shape = parameters["shapes"][0] 52 input1_shape = parameters["shapes"][1] 53 equation = parameters["shapes"][2] 56 dtype=parameters["dtype"], shape=input0_shape) 58 dtype=parameters["dtype"], shape=input1_shape) 62 def build_inputs(parameters, sess, inputs, outputs): argument 64 input0_shape = parameters["shapes"][0] 65 input1_shape = parameters["shapes"][1] 66 input0_value = create_tensor_data(parameters["dtype"], input0_shape) [all …]
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A D | shape_to_strided_slice.py | 31 def build_graph(parameters): argument 34 dtype=parameters["dtype"], 36 shape=parameters["dynamic_input_shape"]) 37 begin = parameters["begin"] 38 end = parameters["end"] 39 strides = parameters["strides"] 46 begin_mask=parameters["begin_mask"], 47 end_mask=parameters["end_mask"]) 50 def build_inputs(parameters, sess, inputs, outputs): argument 53 parameters["dtype"], [all …]
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A D | where_v2.py | 73 def build_graph(parameters): argument 78 shape=parameters["input_condition_shape"]) 80 dtype=parameters["input_dtype"], 82 shape=parameters["input_shape_set"][0]) 84 dtype=parameters["input_dtype"], 86 shape=parameters["input_shape_set"][1]) 90 def build_inputs(parameters, sess, inputs, outputs): argument 93 input_value1 = create_tensor_data(parameters["input_dtype"], 94 parameters["input_shape_set"][0]) 95 input_value2 = create_tensor_data(parameters["input_dtype"], [all …]
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A D | identify_dilated_conv1d.py | 42 def get_tensor_shapes(parameters): argument 43 input_shape = parameters["input_shape"] 44 filter_size = parameters["filter_size"] 45 filter_shape = [filter_size, input_shape[2], parameters["num_filters"]] 48 def build_graph(parameters): argument 50 input_shape, filter_shape = get_tensor_shapes(parameters) 60 stride=parameters["stride"], 61 dilations=parameters["dilations"], 62 padding=parameters["padding"]) 65 def build_inputs(parameters, sess, inputs, outputs): argument [all …]
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A D | tensor_list_length.py | 39 def build_graph(parameters): argument 42 dtype=parameters["element_dtype"], 43 shape=[parameters["num_elements"]] + parameters["element_shape"]) 45 parameters["element_shape"]) 49 def build_inputs(parameters, sess, inputs, outputs): argument 50 data = create_tensor_data(parameters["element_dtype"], 51 [parameters["num_elements"]] + 52 parameters["element_shape"])
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A D | cumsum.py | 38 def build_graph(parameters): argument 41 dtype=parameters["dtype"], shape=parameters["shape"]) 44 parameters["axis"], 45 exclusive=parameters["exclusive"], 46 reverse=parameters["reverse"]) 49 def build_inputs(parameters, sess, inputs, outputs): argument 50 input1 = create_tensor_data(parameters["dtype"], parameters["shape"])
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A D | stft.py | 39 def build_graph(parameters): argument 41 dtype=parameters["input_dtype"], 43 shape=parameters["input_shape"]) 46 frame_length=parameters["frame_length"], 47 frame_step=parameters["frame_step"], 48 fft_length=parameters["fft_length"]) 51 def build_inputs(parameters, sess, inputs, outputs): argument 52 input_value = create_tensor_data(parameters["input_dtype"], 53 parameters["input_shape"])
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A D | irfft2d.py | 47 def build_graph(parameters): argument 49 dtype=parameters["input_dtype"], 51 shape=parameters["input_shape"]) 52 outs = tf.signal.irfft2d(input_value, fft_length=parameters["fft_length"]) 55 def build_inputs(parameters, sess, inputs, outputs): argument 57 rfft_length.append(parameters["input_shape"][-2]) 58 rfft_length.append((parameters["input_shape"][-1] - 1) * 2) 59 rfft_input = create_tensor_data(np.float32, parameters["input_shape"])
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A D | rfft.py | 37 def build_graph(parameters): argument 39 dtype=parameters["input_dtype"], 41 shape=parameters["input_shape"]) 42 outs = tf.signal.rfft(input_value, fft_length=parameters["fft_length"]) 45 def build_inputs(parameters, sess, inputs, outputs): argument 46 input_value = create_tensor_data(parameters["input_dtype"], 47 parameters["input_shape"])
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A D | rfft2d.py | 40 def build_graph(parameters): argument 42 dtype=parameters["input_dtype"], 44 shape=parameters["input_shape"]) 45 outs = tf.signal.rfft2d(input_value, fft_length=parameters["fft_length"]) 48 def build_inputs(parameters, sess, inputs, outputs): argument 49 input_value = create_tensor_data(parameters["input_dtype"], 50 parameters["input_shape"])
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A D | broadcast_gradient_args.py | 37 def build_graph(parameters): argument 39 input1 = tf.compat.v1.placeholder(dtype=parameters['dtype'], name='input1') 40 input2 = tf.compat.v1.placeholder(dtype=parameters['dtype'], name='input2') 44 def build_inputs(parameters, sess, inputs, outputs): argument 45 dtype = parameters['dtype'].as_numpy_dtype() 47 if parameters['input_case'] == 'ALL_EQUAL': 52 elif parameters['input_case'] == 'ONE_DIM': 57 elif parameters['input_case'] == 'NON_BROADCASTABLE':
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A D | broadcast_to.py | 50 def build_graph(parameters): argument 53 dtype=parameters["input_dtype"], 55 shape=parameters["input_shape"]) 57 out = tf.broadcast_to(input_tensor, shape=parameters["output_shape"]) 60 def build_inputs(parameters, sess, inputs, outputs): argument 62 create_tensor_data(parameters["input_dtype"], parameters["input_shape"])
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/AliOS-Things-master/components/lwip/lwip2.0.0/apps/iperf/ |
A D | iperf_task.c | 239 if ( parameters ) { in iperf_udp_run_server() 270 if ( parameters ) { in iperf_udp_run_server() 451 if ( parameters ) { in iperf_udp_run_server() 517 if ( parameters ) { in iperf_tcp_run_server() 634 if ( parameters ) { in iperf_tcp_run_server() 733 if ( parameters ) { in iperf_tcp_run_client() 759 if ( parameters ) { in iperf_tcp_run_client() 812 if ( parameters ) { in iperf_tcp_run_client() 935 if ( parameters ) { in iperf_udp_run_client() 968 if ( parameters ) { in iperf_udp_run_client() [all …]
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/AliOS-Things-master/components/oss/src/model/ |
A D | ListMultipartUploadsRequest.cc | 82 ParameterCollection parameters; in specialParameters() local 83 parameters["uploads"] = ""; in specialParameters() 85 parameters["delimiter"] = delimiter_; in specialParameters() 89 parameters["max-uploads"] = std::to_string(maxUploads_); in specialParameters() 93 parameters["key-marker"] = keyMarker_; in specialParameters() 95 parameters["upload-id-marker"] = uploadIdMarker_; in specialParameters() 100 parameters["prefix"] = prefix_; in specialParameters() 104 parameters["encoding-type"] = encodingType_; in specialParameters() 106 return parameters; in specialParameters()
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