/AliOS-Things-master/solutions/tflite_micro_speech_demo/micro_speech/train/speech_commands/ |
A D | models.py | 24 import tensorflow as tf namespace 160 saver = tf.compat.v1.train.Saver(tf.compat.v1.global_variables()) 190 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') 256 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') 380 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') 398 first_conv = tf.nn.conv2d( 518 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') 713 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') 731 first_conv = tf.nn.conv2d( 818 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate') [all …]
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A D | input_data.py | 33 import tensorflow as tf namespace 127 with tf.compat.v1.Session(graph=tf.Graph()) as sess: 128 wav_filename_placeholder = tf.compat.v1.placeholder(tf.string, []) 144 with tf.compat.v1.Session(graph=tf.Graph()) as sess: 145 wav_filename_placeholder = tf.compat.v1.placeholder(tf.string, []) 146 sample_rate_placeholder = tf.compat.v1.placeholder(tf.int32, []) 147 wav_data_placeholder = tf.compat.v1.placeholder(tf.float32, [None, 1]) 355 with tf.compat.v1.Session(graph=tf.Graph()) as sess: 472 int16_input = tf.cast(tf.multiply(background_clamp, 32768), tf.int16) 484 tf.expand_dims(tf.expand_dims(self.output_, -1), 0), [all …]
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A D | train.py | 79 import tensorflow as tf namespace 93 sess = tf.compat.v1.InteractiveSession() 168 with tf.compat.v1.name_scope('train'), tf.control_dependencies( 186 evaluation_step = tf.reduce_mean(input_tensor=tf.cast(correct_prediction, 195 saver = tf.compat.v1.train.Saver(tf.compat.v1.global_variables()) 254 tf.compat.v1.logging.debug( 260 tf.compat.v1.logging.info( 490 return tf.compat.v1.logging.DEBUG 492 return tf.compat.v1.logging.INFO 494 return tf.compat.v1.logging.WARN [all …]
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A D | freeze.py | 45 import tensorflow as tf namespace 96 wav_data_placeholder = tf.compat.v1.placeholder(tf.string, [], 98 decoded_sample_data = tf.audio.decode_wav( 110 fingerprint_input = tf.nn.pool( 133 int16_input = tf.cast( 134 tf.multiply(decoded_sample_data.audio, 32767), tf.int16) 142 out_type=tf.float32) 168 tf.io.write_graph( 214 _ = tf.contrib 224 sess = tf.compat.v1.InteractiveSession() [all …]
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A D | test_streaming_accuracy.py | 70 import tensorflow as tf namespace 82 graph = tf.Graph() 84 od_graph_def = tf.compat.v1.GraphDef() 85 with tf.io.gfile.GFile(mode_file, 'rb') as fid: 88 tf.import_graph_def(od_graph_def, name='') 103 with tf.compat.v1.Session(graph=tf.Graph()) as sess: 104 wav_filename_placeholder = tf.compat.v1.placeholder(tf.string, []) 135 with tf.compat.v1.Session() as sess: 172 tf.compat.v1.logging.error( 175 tf.compat.v1.logging.info('{}ms {}:{}{}'.format( [all …]
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A D | label_wav.py | 37 import tensorflow as tf namespace 45 with tf.io.gfile.GFile(filename, 'rb') as f: 46 graph_def = tf.compat.v1.GraphDef() 48 tf.import_graph_def(graph_def, name='') 53 return [line.rstrip() for line in tf.io.gfile.GFile(filename)] 59 with tf.compat.v1.Session() as sess: 79 if not wav or not tf.io.gfile.exists(wav): 81 if not labels or not tf.io.gfile.exists(labels): 84 if not graph or not tf.io.gfile.exists(graph): 129 tf.compat.v1.app.run(main=main, argv=[sys.argv[0]] + unparsed)
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A D | label_wav_dir.py | 38 import tensorflow as tf namespace 46 with tf.io.gfile.GFile(filename, 'rb') as f: 47 graph_def = tf.compat.v1.GraphDef() 49 tf.import_graph_def(graph_def, name='') 54 return [line.rstrip() for line in tf.io.gfile.GFile(filename)] 60 with tf.compat.v1.Session() as sess: 66 if not wav_path or not tf.io.gfile.exists(wav_path): 87 if not labels or not tf.io.gfile.exists(labels): 90 if not graph or not tf.io.gfile.exists(graph): 132 tf.compat.v1.app.run(main=main, argv=[sys.argv[0]] + unparsed)
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A D | label_wav_test.py | 23 import tensorflow as tf namespace 33 sample_data = tf.zeros([1000, 2]) 34 wav_encoder = tf.audio.encode_wav(sample_data, 16000) 50 with tf.compat.v1.Session() as sess: 51 tf.compat.v1.placeholder(tf.string, name=input_name) 52 tf.zeros([1, 3], name=output_name)
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/AliOS-Things-master/components/ai_agent/src/engine/tflite-micro/tensorflow/lite/experimental/mlir/testing/op_tests/ |
A D | where_v2.py | 20 import tensorflow.compat.v1 as tf namespace 33 "input_dtype": [tf.float32, tf.int32], 38 "input_dtype": [tf.float32, tf.int32], 43 "input_dtype": [tf.float32, tf.int32], 48 "input_dtype": [tf.float32, tf.int32], 53 "input_dtype": [tf.float32, tf.int32], 58 "input_dtype": [tf.float32, tf.int32], 63 "input_dtype": [tf.float32, tf.int32], 68 "input_dtype": [tf.float32, tf.int32], 76 dtype=tf.bool, [all …]
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A D | parse_example.py | 23 import tensorflow.compat.v1 as tf namespace 33 if feature_dtype in (tf.float32, tf.float16, tf.float64): 35 features["x"] = tf.train.Feature( 37 elif feature_dtype in (tf.int32, tf.uint8, tf.int64, tf.int16): 39 features["x"] = tf.train.Feature( 41 elif feature_dtype == tf.string: 44 features["x"] = tf.train.Feature( 46 example = tf.train.Example(features=tf.train.Features(feature=features)) 56 "feature_dtype": [tf.string, tf.float32, tf.int64], 66 input_value = tf.compat.v1.placeholder( [all …]
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A D | broadcast_to.py | 20 import tensorflow as tf namespace 32 "input_dtype": [tf.float32, tf.int32], 37 "input_dtype": [tf.float32, tf.int32], 41 "input_dtype": [tf.float32, tf.int32], 45 "input_dtype": [tf.float32, tf.int32], 52 input_tensor = tf.compat.v1.placeholder( 57 out = tf.broadcast_to(input_tensor, shape=parameters["output_shape"])
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A D | static_hashtable.py | 20 import tensorflow.compat.v1 as tf namespace 33 "table": [(tf.string, tf.int64, ["1", "2", "3"], [4, 5, 6], -1), 34 (tf.int64, tf.string, [1, 2, 3], ["4", "5", "6"], "-1")], 42 key_tensor = tf.constant(keys, dtype=key_dtype) 43 value_tensor = tf.constant(values, dtype=value_dtype) 45 initializer = tf.lookup.KeyValueTensorInitializer(key_tensor, value_tensor) 46 table = tf.lookup.StaticHashTable(initializer, default_value) 48 with tf.control_dependencies([tf.initializers.tables_initializer()]): 49 input_value = tf.compat.v1.placeholder(
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A D | while_loop.py | 21 import tensorflow.compat.v1 as tf namespace 36 "dtype": [tf.int32], 40 "dtype": [tf.string], 49 num_iterations = tf.placeholder( 50 dtype=tf.int32, name="num_iterations", shape=(1,)) 51 increment_value = tf.placeholder( 53 num_iterations_scalar = tf.reshape(num_iterations, ()) 69 if parameters["dtype"] == tf.string: 72 new_value = tf.fill([1], tf.reshape(increment_value, ())) 77 counter, value, result_increment_value = tf.while_loop(
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A D | control_dep.py | 20 import tensorflow.compat.v1 as tf namespace 37 input_tensor = tf.compat.v1.placeholder( 38 dtype=tf.float32, name="input", shape=parameters["input_shape"]) 39 filter_value = tf.zeros((3, 3, TEST_INPUT_DEPTH, 8), tf.float32) 40 assert_op = tf.compat.v1.assert_greater_equal(input_tensor, 42 with tf.control_dependencies([assert_op]): 43 out = tf.nn.conv2d( 48 input_values = create_tensor_data(tf.float32, parameters["input_shape"])
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A D | cond.py | 21 import tensorflow.compat.v1 as tf namespace 38 "dtype": [tf.float32, tf.string], 44 input1 = tf.placeholder(dtype=parameters["dtype"], shape=(1,)) 45 input2 = tf.placeholder(dtype=parameters["dtype"], shape=(1,)) 50 pred = tf.placeholder(dtype=tf.bool, shape=(1,)) 51 pred_scalar = tf.reshape(pred, ()) 53 out = tf.cond(pred_scalar, lambda: input1, lambda: input2)
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A D | static_rnn_with_control_flow_v2.py | 20 import tensorflow.compat.v1 as tf namespace 35 "dtype": [tf.float32], 53 one_timestamp_input = tf.placeholder( 58 lstm_cell = tf.nn.rnn_cell.BasicLSTMCell( 59 num_cells, activation=tf.nn.relu, state_is_tuple=True) 70 dtype=tf.float32, 78 with tf.variable_scope("", reuse=True): 79 kernel = tf.get_variable("rnn/basic_lstm_cell/kernel") 80 bias = tf.get_variable("rnn/basic_lstm_cell/bias") 86 sess.run(tf.group(kernel.assign(kernel_values), bias.assign(bias_values)))
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A D | tensor_list_dynamic_shape.py | 20 import tensorflow.compat.v1 as tf namespace 33 "element_dtype": [tf.float32, tf.int32], 41 item = tf.placeholder( 52 new_item = tf.add( 53 tf.add(item, item), 54 tf.constant(value=1, dtype=parameters["element_dtype"])) 58 _, tensor_list = tf.while_loop(condition, loop_body, init_state)
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A D | complex_abs.py | 20 import tensorflow.compat.v1 as tf namespace 32 "dtype": [tf.complex64], 34 "Tout": [tf.float32] 36 "dtype": [tf.complex128], 38 "Tout": [tf.float64] 42 input_tensor = tf.compat.v1.placeholder( 46 out = tf.raw_ops.ComplexAbs(x=input_tensor, Tout=parameters["Tout"])
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A D | segment_sum.py | 20 import tensorflow.compat.v1 as tf namespace 33 "data_dtype": [tf.float32, tf.int32], 41 data = tf.compat.v1.placeholder( 45 segment_ids = tf.constant(parameters["segment_ids"], dtype=tf.int32) 46 out = tf.segment_sum(data, segment_ids)
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A D | dense_image_warp.py | 20 import tensorflow as tf namespace 40 input_tensor = tf.compat.v1.placeholder( 41 dtype=tf.float32, name='input', shape=parameters['input_size']) 42 flow_tensor = tf.compat.v1.placeholder( 43 dtype=tf.float32, name='flow', shape=parameters['flow_size']) 50 tf.float32, parameters['input_size'], min_value=-10, max_value=10), 52 tf.float32, parameters['flow_size'], min_value=-10, max_value=10)
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A D | reciprocal.py | 20 import tensorflow.compat.v1 as tf namespace 32 "input_dtype": [tf.float32, tf.int32, tf.int64], 38 input_tensor = tf.compat.v1.placeholder( 43 out = tf.math.reciprocal(input_tensor)
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A D | conv_bias_activation.py | 21 import tensorflow.compat.v1 as tf namespace 68 @tf.function(jit_compile=True) 70 out = tf.nn.conv2d( 81 out = tf.nn.bias_add(data_input, bias_input, data_format="NHWC") 87 input_tensor = tf.compat.v1.placeholder( 88 dtype=tf.float32, name="input", shape=input_shape) 97 out = tf.nn.conv2d( 115 out = tf.nn.conv2d( 149 return make_conv_bias_activation_tests(tf.nn.relu6)(options)
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/AliOS-Things-master/components/ai_agent/src/engine/tflite-micro/tensorflow/lite/micro/testing/ |
A D | generate_test_models.py | 31 import tensorflow as tf namespace 42 model = tf.keras.models.Sequential() 45 model.add(tf.keras.layers.Conv2D(32, 3, activation="relu")) 46 model.add(tf.keras.layers.MaxPooling2D(2)) 47 model.add(tf.keras.layers.Flatten()) 48 model.add(tf.keras.layers.Dense(10)) 63 converter = tf.lite.TFLiteConverter.from_keras_model(model) 64 converter.optimizations = [tf.lite.Optimize.DEFAULT] 65 converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8] 66 converter.inference_input_type = tf.int8 [all …]
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/AliOS-Things-master/components/SDL2/src/image/external/tiff-4.0.9/libtiff/ |
A D | tif_aux.c | 97 tf[0] = tf[1] = tf[2] = 0; in TIFFDefaultTransferFunction() 104 if (tf[0] == NULL) in TIFFDefaultTransferFunction() 106 tf[0][0] = 0; in TIFFDefaultTransferFunction() 114 if(tf[1] == NULL) in TIFFDefaultTransferFunction() 116 _TIFFmemcpy(tf[1], tf[0], nbytes); in TIFFDefaultTransferFunction() 120 _TIFFmemcpy(tf[2], tf[0], nbytes); in TIFFDefaultTransferFunction() 125 if (tf[0]) in TIFFDefaultTransferFunction() 126 _TIFFfree(tf[0]); in TIFFDefaultTransferFunction() 127 if (tf[1]) in TIFFDefaultTransferFunction() 129 if (tf[2]) in TIFFDefaultTransferFunction() [all …]
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/AliOS-Things-master/components/ai_agent/src/engine/tflite-micro/tensorflow/lite/experimental/microfrontend/python/kernel_tests/ |
A D | audio_microfrontend_op_test.py | 21 import tensorflow as tf namespace 43 audio = tf.constant( 45 tf.int16) 61 audio = tf.constant( 63 tf.int16) 82 audio = tf.constant( 84 tf.int16) 104 tf.int16) 126 tf.int16) 146 tf.int16) [all …]
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