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[Bridgetower] Fix for Nonetype in image #39

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[Bridgetower] Fix for Nonetype in image #39

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984ff3f
[SW-174850] Fix for Nonetype in image
MohitIntel Feb 14, 2024
cd531e8
Using media external reader API
MohitIntel Feb 15, 2024
c0638e5
minor fixes
MohitIntel Feb 16, 2024
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59 changes: 22 additions & 37 deletions examples/contrastive-image-text/clip_media_pipe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,28 +24,33 @@

try:
from habana_frameworks.mediapipe import fn
from habana_frameworks.mediapipe.backend.nodes import opnode_tensor_info
from habana_frameworks.mediapipe.backend.operator_specs import schema
from habana_frameworks.mediapipe.media_types import dtype, ftype, imgtype, randomCropType, readerOutType
from habana_frameworks.mediapipe.mediapipe import MediaPipe
from habana_frameworks.mediapipe.operators.media_nodes import MediaReaderNode
from habana_frameworks.mediapipe.operators.reader_nodes.reader_nodes import media_ext_reader_op_impl
from habana_frameworks.mediapipe.operators.reader_nodes.read_image_from_dir import get_max_file
from habana_frameworks.mediapipe.operators.reader_nodes.reader_nodes import media_ext_reader_op_tensor_info
from habana_frameworks.torch.hpu import get_device_name
except ImportError:
pass

read_image_text_from_dataset_params = {
"label_dtype": dtype.UINT64,
"dataset": None,
}

class read_image_text_from_dataset(MediaReaderNode):
class read_clip_data(media_ext_reader_op_impl):
"""
Class defining read image/text from directory node.
Class defining read image/text from clip dataset.

"""

def __init__(self, name, guid, device, inputs, params, cparams, node_attr):
super().__init__(name, guid, device, inputs, params, cparams, node_attr)
def __init__(self, params):
self.batch_size = 1
params = params['priv_params']
self.meta_dtype = params["label_dtype"]
self.dataset = params["dataset"]
self.epoch = 0
self.batch_sampler_iter = None

self.num_imgs_slice = len(ClipMediaPipe.batch_sampler.sampler)
self.num_batches_slice = len(ClipMediaPipe.batch_sampler)
Expand All @@ -57,18 +62,16 @@ def __init__(self, name, guid, device, inputs, params, cparams, node_attr):
self.max_file = get_max_file([img["path"] for img in self.dataset["image"]])
logger.info(f"The largest file is {self.max_file}.")

self.iter_loc = 0

def set_params(self, params):
self.batch_size = params.batch_size

def gen_output_info(self):
out_info = []
o = opnode_tensor_info(dtype.NDT, np.array([self.batch_size], dtype=np.uint32), "")
out_info.append(o)
o = opnode_tensor_info(
self.meta_dtype, np.array([self.dataset.text_max_length, self.batch_size], dtype=np.uint32), ""
)
o = media_ext_reader_op_tensor_info(dtype.NDT, np.array([self.batch_size], dtype=np.uint32), "")
out_info.append(o)
o = opnode_tensor_info(
o = media_ext_reader_op_tensor_info(
self.meta_dtype, np.array([self.dataset.text_max_length, self.batch_size], dtype=np.uint32), ""
)
out_info.append(o)
Expand Down Expand Up @@ -111,28 +114,6 @@ def __next__(self):

return img_list, input_id_list, attention_mask_list


read_image_text_from_dataset_params = {
"label_dtype": dtype.UINT64,
"dataset": None,
}
schema.add_operator(
"ClipDataReader",
None,
0,
0,
[],
3,
read_image_text_from_dataset_params,
None,
read_image_text_from_dataset,
dtype.NDT,
)
op_class = fn.operator_add("ClipDataReader")
op_class.__module__ = fn.__name__
setattr(fn, "ClipDataReader", op_class)


class ClipMediaPipe(MediaPipe):
"""
Class defining clip media pipe:
Expand Down Expand Up @@ -160,8 +141,12 @@ def __init__(self, dataset=None, sampler=None, batch_size=512, drop_last=False,
super(ClipMediaPipe, self).__init__(
device=self.device, batch_size=batch_size, prefetch_depth=queue_depth, pipe_name=pipe_name
)

self.input = fn.ClipDataReader(label_dtype=dtype.UINT32, dataset=self.dataset)
params = read_image_text_from_dataset_params.copy()
params['dataset'] = self.dataset
self.input = fn.MediaExtReaderOp(impl=read_clip_data,
num_outputs=3,
priv_params=params,
)
def_output_image_size = [self.image_size, self.image_size]
res_pp_filter = ftype.BICUBIC
self.decode = fn.ImageDecoder(
Expand Down