(tensorflow-1.12.0-src) kaos-new:plaid-maskrcnn sam$ python dirty.py
Traceback (most recent call last):
File "dirty.py", line 49, in <module>
rep = onnx_plaidml.backend.prepare(model, device='GPU')
File "/Users/sam/dev/virtualenv/tensorflow-1.12.0-src/lib/python3.6/site-packages/onnx_plaidml/backend.py", line 249, in prepare
ops = _load_ops(model.opset_import)
File "/Users/sam/dev/virtualenv/tensorflow-1.12.0-src/lib/python3.6/site-packages/onnx_plaidml/backend.py", line 77, in _load_ops
domain, version)), None)
File "<string>", line 3, in raise_from
NotImplementedError: ""/version=10" is not implemented by the PlaidML ONNX backend
When running the following test code
import onnx
import onnx_plaidml.backend
import onnx.numpy_helper
data_path = "//Users/sam/dev/plaid-maskrcnn/test_data_set_0/input_0.pb"
tensor = onnx.TensorProto()
with open(data_path, 'rb') as f:
tensor.ParseFromString(f.read())
x = onnx.numpy_helper.to_array(tensor)
model_path = "/Users/sam/dev/plaid-maskrcnn/mask_rcnn_R_50_FPN_1x.onnx"
model = onnx.load(model_path)
import numpy as np
from PIL import Image
def preprocess(image):
# Resize
ratio = 800.0 / min(image.size[0], image.size[1])
image = image.resize((int(ratio * image.size[0]), int(ratio * image.size[1])), Image.BILINEAR)
# Convert to BGR
image = np.array(image)[:, :, [2, 1, 0]].astype('float32')
# HWC -> CHW
image = np.transpose(image, [2, 0, 1])
# Normalize
mean_vec = np.array([102.9801, 115.9465, 122.7717])
for i in range(image.shape[0]):
image[i, :, :] = image[i, :, :] - mean_vec[i]
# Pad to be divisible of 32
import math
padded_h = int(math.ceil(image.shape[1] / 32) * 32)
padded_w = int(math.ceil(image.shape[2] / 32) * 32)
padded_image = np.zeros((3, padded_h, padded_w), dtype=np.float32)
padded_image[:, :image.shape[1], :image.shape[2]] = image
image = padded_image
return image
img = Image.open('/Users/sam/Downloads/VER01_010_plateD_v0001.1008.png')
img_data = preprocess(img)
rep = onnx_plaidml.backend.prepare(model, device='GPU')
for batch in range(1):
data = img['inputs'][batch, :]
output = rep.run([data])
print(output)
Just trying to see if it possible to run maskrcnn on plaidml for GPU acceleration on a non NVIDIA GPU.
But it seems that onnx-plaidml is no longer maintained.
I got the following error
When running the following test code
Just trying to see if it possible to run maskrcnn on plaidml for GPU acceleration on a non NVIDIA GPU.
But it seems that onnx-plaidml is no longer maintained.