Upgrading tensorflow-macos and tensorflow-metal breaks Conv2d with groups arg

Question

wangcheng OP

Created May ’22

Replies 3

Boosts 3

Views 2k

Participants 6

Today I upgraded tensorflow-macos to 2.9.0 and tensorflow-metal to 0.5.0, and found my old notebook failed to run.

It ran well with tensorflow-macos 2.8.0 and tensorflow-metal 0.4.0.

Specifically, I found that the groups arg of Conv2d layer was the cause.

Here is a demo:

 import tensorflow as tf
from tensorflow import keras as tfk
 
# tf.config.set_visible_devices([], 'GPU')
 
Xs = tf.random.normal((32, 64, 48, 4))
ys = tf.random.normal((32,))
 
tf.random.set_seed(0)
 
model = tfk.Sequential([
    tfk.layers.Conv2D(
        filters=16,
        kernel_size=(4, 3), 
        groups=4, # groups arg
        activation='relu',
    ),
    tfk.layers.Flatten(),
    tfk.layers.Dense(1, activation='sigmoid'),
])
 
model.compile(
    loss=tfk.losses.BinaryCrossentropy(),
    metrics=[
        tfk.metrics.BinaryAccuracy(),
    ],
)
 
model.fit(Xs, ys, epochs=2, verbose=1)

The error is:

W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at xla_ops.cc:296 : UNIMPLEMENTED: Could not find compiler for platform METAL: NOT_FOUND: could not find registered compiler for platform METAL -- check target linkage

Removing groups arg would make the code run again.

Training on CPU, by uncommenting line 4, gives different error:

 'apple-m1' is not a recognized processor for this target (ignoring processor)
 
LLVM ERROR: 64-bit code requested on a subtarget that doesn't support it!

And removing groups arg also would make training on CPU work. However I didn't test training on CPU before the upgrade.

My device is a MacBook Pro 14' running macOS 12.4.

Boost

Answer 1

Frameworks Engineer OP

Apple

Jun ’22

Hi @wangcheng

Thanks for reporting the problem. I am seeing the same behavior locally and will investigate what has caused this issue.

0

Answer 2

lukasf98 OP

Feb ’23

Are there any updates? I'm trying to train MelGAN from the Kerns examples which uses groups in Conv1D. I get the same error with tensorflow-macos 2.11.0 and tensorflow-metal 0.7.1.

0

Answer 3

clarkmcc OP

Feb ’23

I'm getting this same error when running this notebook locally: https://colab.research.google.com/github/google/eng-edu/blob/main/ml/cc/exercises/linear_regression_with_synthetic_data.ipynb?utm_source=mlcc&utm_campaign=colab-external&utm_medium=referral&utm_content=linear_regression_synthetic_tf2-colab&hl=en#scrollTo=SIpsyJITPcbG

0

	import tensorflow as tf
	from tensorflow import keras as tfk

	# tf.config.set_visible_devices([], 'GPU')

	Xs = tf.random.normal((32, 64, 48, 4))
	ys = tf.random.normal((32,))

	tf.random.set_seed(0)

	model = tfk.Sequential([
	tfk.layers.Conv2D(
	filters=16,
	kernel_size=(4, 3),
	groups=4, # groups arg
	activation='relu',
	),
	tfk.layers.Flatten(),
	tfk.layers.Dense(1, activation='sigmoid'),
	])

	model.compile(
	loss=tfk.losses.BinaryCrossentropy(),
	metrics=[
	tfk.metrics.BinaryAccuracy(),
	],
	)

	model.fit(Xs, ys, epochs=2, verbose=1)

	'apple-m1' is not a recognized processor for this target (ignoring processor)

	LLVM ERROR: 64-bit code requested on a subtarget that doesn't support it!