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Reply to tensorflow-macos slow (Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.)
Same issue: Monterey 12.0.1. MacBook Pro 14" M1 10 core CPU 14 Core GPU. Followed https://developer.apple.com/metal/tensorflow-plugin/ here. GPU execution is very slow compared to CPU. Code is: import tensorflow as tf import time with tf.device('/CPU:0'): start = time.time() mnist = tf.keras.datasets.mnist (x_train, y_train),(x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation='softmax') ]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) model.fit(x_train, y_train, epochs=5) model.evaluate(x_test, y_test) result = time.time()-start print("Total time: {:0.2f}ms".format(1000*result)) with tf.device('/GPU:0'): start = time.time() mnist = tf.keras.datasets.mnist (x_train, y_train),(x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation='softmax') ]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) model.fit(x_train, y_train, epochs=5) model.evaluate(x_test, y_test) result = time.time()-start print("Total time: {:0.2f}ms".format(1000*result))
Oct ’21