Open maciej3031 opened 2 years ago
TobyRoseman
commented
2 years ago I'm not able to reproduce this problem. I get the following TensorFlow error by just declaring your class:
AlreadyExistsError: Another metric with the same name already exists.
maciej3031
commented
2 years ago Hey, that's very strange, everything works fine for me. To reproduce it once again I used the following commands:
conda create -n test_env python=3.9conda activate test_envconda install tensorflow==2.6.0python3.9 -m pip install coremltoolsconda install pillowpython3.9 coreml.py where coreml.py is:
import os
import numpy as np
import tensorflow as tf
import coremltools as ct
from PIL import Imageimg01 = np.random.rand(256, 256, 3).astype(np.float32) img0255 = (img01*255).astype(np.uint8) img_pil = Image.fromarray(img0255)
class ProblemLayer(tf.keras.layers.Layer): def init(self, kwargs): super(ProblemLayer, self).init(kwargs)
def call(self, image):
B, H, W = tf.shape(image)[0], tf.shape(image)[1], tf.shape(image)[2]
proj_mat = tf.convert_to_tensor([[1.22, 0.09, -39.61, -0.09, 1.22, -6.17, 0.0, 0.0]], dtype=tf.float32)
proj_mat = tf.repeat(proj_mat, B, 0)
image = tf.raw_ops.ImageProjectiveTransformV2(
images=image,
transforms=proj_mat,
output_shape=[H, W],
interpolation='BILINEAR',
fill_mode='CONSTANT')
return imageinp = tf.keras.layers.Input(shape=(256, 256, 3), name="combined_input") x = ProblemLayer()(inp) model = tf.keras.models.Model(inputs=inp, outputs=x)
mlmodel = ct.convert(model, inputs=[ct.ImageType(shape=(1, 256, 256, 3), scale=1.0/255.0)], convert_to="mlprogram")
pred_coreml = mlmodel.predict({'combined_input': img_pil})
and the error is still:Traceback (most recent call last):
File "/Users/maciej3031/projects/coreml.py", line 33, in
I think you're using non-standard conda channels. When running step 3, I get a PackagesNotFoundError.
If I follow your directions but install TensorFlow 2.6.0 using pip, I get the same error as before when declaring your class.
maciej3031
commented
2 years ago I use mini conda forge from https://developer.apple.com/metal/tensorflow-plugin/ and tensorflow: conda-forge/osx-arm64::tensorflow-2.6.0-py39hb1906d9_1
maciej3031
commented
2 years ago Did anyone succeed to reproduce it?
TobyRoseman
commented
2 years ago Ok, so you're on an M1 machine and using tensorflow-metal, those are important details.
Did anyone succeed to reproduce it?
Yes, using tensorflow-metal on an M1 machine, I can reproduce this problem.
maciej3031
commented
2 years ago Yes, it's on M1. However, it occurs on both tensorflow-metal and usual tensorflow.
🐞Describe the bug
When you have an ImageProjectiveTransformV2 op in tensorflow model and try to convert it to coreml then it raises the following exception. Is seems that
affineops does not support the "unnormalized"coordinates_mode. Do you plan to fix it in the near future? Affine transformation is quite commonly used in computer vision problems nowadays and it would be really nice to use it during conversion from tensorflow 🙏Trace
Minimal code to Reproduce
System environment
Additional context
Apart from this bug, do you plan to add support for ImageProjectiveTransformV3?