| /AliOS-Things-master/solutions/tflite_micro_speech_demo/micro_speech/train/speech_commands/ |
| A D | freeze_test.py | 34 with self.cached_session() as sess:
47 sess.graph.get_tensor_by_name('decoded_sample_data:0'))
49 ops = [node.op for node in sess.graph_def.node]
54 with self.cached_session() as sess:
67 sess.graph.get_tensor_by_name('decoded_sample_data:0'))
69 ops = [node.op for node in sess.graph_def.node]
74 with self.cached_session() as sess:
92 with self.cached_session() as sess:
107 ops = [node.op for node in sess.graph_def.node]
114 with self.cached_session() as sess:
[all …]
|
| A D | models_test.py | 54 with self.cached_session() as sess:
60 self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
61 self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_rate.name))
66 with self.cached_session() as sess:
71 self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
76 with self.cached_session() as sess:
82 self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
88 with self.cached_session() as sess:
94 self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
109 with self.cached_session() as sess:
[all …]
|
| A D | test_streaming_accuracy.py | 103 with tf.compat.v1.Session(graph=tf.Graph()) as sess:
107 res = sess.run(wav_decoder, feed_dict={wav_filename_placeholder: filename})
135 with tf.compat.v1.Session() as sess:
138 data_tensor = sess.graph.get_tensor_by_name(FLAGS.input_names[0])
139 sample_rate_tensor = sess.graph.get_tensor_by_name(FLAGS.input_names[1])
140 output_softmax_tensor = sess.graph.get_tensor_by_name(FLAGS.output_name)
146 outputs = sess.run(
|
| A D | train.py | 93 sess = tf.compat.v1.InteractiveSession()
200 sess.graph)
209 models.load_variables_from_checkpoint(sess, FLAGS.start_checkpoint)
210 start_step = global_step.eval(session=sess)
215 tf.io.write_graph(sess.graph_def, FLAGS.train_dir,
237 FLAGS.background_volume, time_shift_samples, 'training', sess)
239 train_summary, train_accuracy, cross_entropy_value, _, _ = sess.run(
270 0.0, 0, 'validation', sess))
273 validation_summary, validation_accuracy, conf_matrix = sess.run(
298 saver.save(sess, checkpoint_path, global_step=training_step)
[all …]
|
| A D | freeze.py | 176 def save_saved_model(file_name, sess, input_tensor, output_tensor): argument
200 sess,
224 sess = tf.compat.v1.InteractiveSession()
231 models.load_variables_from_checkpoint(sess, FLAGS.start_checkpoint)
235 sess, sess.graph_def, ['labels_softmax'])
240 save_saved_model(FLAGS.output_file, sess, input_tensor, output_tensor)
|
| A D | input_data.py | 127 with tf.compat.v1.Session(graph=tf.Graph()) as sess:
131 return sess.run(
144 with tf.compat.v1.Session(graph=tf.Graph()) as sess:
151 sess.run(
355 with tf.compat.v1.Session(graph=tf.Graph()) as sess:
362 wav_data = sess.run(
510 background_volume_range, time_shift, mode, sess): argument
604 summary, data_tensor = sess.run(
612 def get_features_for_wav(self, wav_filename, model_settings, sess): argument
637 data_tensor = sess.run([self.output_], feed_dict=input_dict)
[all …]
|
| A D | label_wav.py | 59 with tf.compat.v1.Session() as sess:
64 softmax_tensor = sess.graph.get_tensor_by_name(output_layer_name)
65 predictions, = sess.run(softmax_tensor, {input_layer_name: wav_data})
|
| A D | label_wav_dir.py | 60 with tf.compat.v1.Session() as sess:
71 softmax_tensor = sess.graph.get_tensor_by_name(output_layer_name)
72 predictions, = sess.run(softmax_tensor, {input_layer_name: wav_data})
|
| /AliOS-Things-master/components/ai_agent/src/engine/tflite-micro/tensorflow/lite/experimental/mlir/testing/op_tests/ |
| A D | dynamic_rnn.py | 58 def build_inputs(parameters, sess, inputs, outputs): argument
60 sess.run(tf.global_variables_initializer())
68 output_values = sess.run(
|
| A D | static_rnn_with_control_flow_v2.py | 75 def build_inputs(parameters, sess, inputs, outputs): argument
86 sess.run(tf.group(kernel.assign(kernel_values), bias.assign(bias_values)))
96 out = sess.run(outputs, feed_dict=dict(zip(inputs, input_values)))
|
| A D | batchmatmul.py | 80 def build_inputs(parameters, sess, inputs, outputs): argument
91 output_values = sess.run(
99 output_values = sess.run(
|
| A D | softplus.py | 45 def build_inputs(parameters, sess, inputs, outputs): argument
53 return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
|
| A D | real.py | 44 def build_inputs(parameters, sess, inputs, outputs): argument
50 return [input_values], sess.run(
|
| A D | imag.py | 44 def build_inputs(parameters, sess, inputs, outputs): argument
50 return [input_values], sess.run(
|
| A D | reciprocal.py | 46 def build_inputs(parameters, sess, inputs, outputs): argument
50 return input_values, sess.run(
|
| A D | rfft.py | 45 def build_inputs(parameters, sess, inputs, outputs): argument
48 return [input_value], sess.run(
|
| A D | rfft2d.py | 48 def build_inputs(parameters, sess, inputs, outputs): argument
51 return [input_value], sess.run(
|
| A D | tensor_list_length.py | 49 def build_inputs(parameters, sess, inputs, outputs): argument
53 return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))
|
| A D | broadcast_to.py | 60 def build_inputs(parameters, sess, inputs, outputs): argument
64 return input_values, sess.run(
|
| A D | complex_abs.py | 49 def build_inputs(parameters, sess, inputs, outputs): argument
55 return [input_values], sess.run(
|
| A D | cumsum.py | 49 def build_inputs(parameters, sess, inputs, outputs): argument
51 return [input1], sess.run(outputs, feed_dict=dict(zip(inputs, [input1])))
|
| A D | segment_sum.py | 49 def build_inputs(parameters, sess, inputs, outputs): argument
52 return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))
|
| A D | stft.py | 51 def build_inputs(parameters, sess, inputs, outputs): argument
54 return [input_value], sess.run(
|
| A D | tensor_list_concat.py | 50 def build_inputs(parameters, sess, inputs, outputs): argument
54 return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))
|
| A D | tensor_list_get_item.py | 51 def build_inputs(parameters, sess, inputs, outputs): argument
55 return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))
|