Support XLA

[Zhaopudark]

It seems do not support XLA (jit compile), such as the following demo:

physical_devices = tf.config.experimental.list_physical_devices(device_type='GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True)
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'],
              jit_compile=True)
model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test,  y_test, verbose=2)

And the bug is shown as:

W tensorflow/core/framework/op_kernel.cc:1780] OP_REQUIRES failed at xla_ops.cc:296 : UNIMPLEMENTED: Could not find compiler for platform DML: NOT_FOUND: could not find registered compiler for platform DML -- was support for that platform linked in?

Thanks in advance. Best wishes.

[PatriceVignola]

DML doesn't support XLA because it is fundamentally different from how the compiler for other backends like CUDA and AMD works. To make the code work, remove the jit_compile=True line above.

[Zhaopudark]

Thanks. 😊