def flips_fn(self, img, lbl):
kwargs = {
"horizontal": fn.coin_flip(probability=0.33),
"vertical": fn.coin_flip(probability=0.33)
}
if self.dim == 3:
kwargs.update({"depthwise": fn.coin_flip(probability=0.33)})
return fn.flip(img, **kwargs), fn.flip(lbl, **kwargs)
def dali_pipeline(source, image_size, training, cpu=False):
images, labels = fn.external_source(source=source, num_outputs=2)
if cpu:
device = "cpu"
images = fn.decoders.image(images, device=device)
else:
device = "gpu"
images = fn.decoders.image(
images,
device="mixed",
device_memory_padding=211025920,
host_memory_padding=140544512,
)
if training:
images = fn.random_resized_crop(
images,
device=device,
size=image_size,
interp_type=types.DALIInterpType.INTERP_CUBIC,
)
coin = fn.random.coin_flip(0.5)
images = fn.flip(images, horizontal=coin)
else:
pass
return images, labels
def reference_pipeline(flip_vertical, flip_horizontal, ref_batch_size=max_batch_size):
pipeline = Pipeline(ref_batch_size, num_threads, device_id)
with pipeline:
data, _ = fn.readers.file(file_root=images_dir)
img = fn.decoders.image(data)
flipped = fn.flip(img, horizontal=flip_horizontal, vertical=flip_vertical)
pipeline.set_outputs(flipped, img)
return pipeline
def pipe(max_batch_size, input_data, device):
pipe = Pipeline(batch_size=max_batch_size, num_threads=4, device_id=0)
depthwise = fn.random.coin_flip()
horizontal = fn.random.coin_flip()
vertical = fn.random.coin_flip()
data = fn.external_source(source=input_data, cycle=False, device=device)
processed = fn.flip(data, depthwise=depthwise, horizontal=horizontal, vertical=vertical)
pipe.set_outputs(processed)
return pipe
def pipeline_runtime(flip_vertical, flip_horizontal):
data, _ = fn.file_reader(file_root=images_dir)
img = fn.image_decoder(data)
flipped = fn.flip(img, horizontal=flip_horizontal, vertical=flip_vertical)
return flipped, img
def flip_1d(x):
# TODO(janton): remove the layout trick when Flip supports arbitrary data layouts
x = fn.reshape(x, shape=(-1, 1, 1), layout="HWC")
x = fn.flip(x, vertical=1)
x = fn.reshape(x, shape=(-1, ), layout="t")
return x
def pipeline_static(flip_vertical, flip_horizontal):
data, _ = fn.readers.file(file_root=images_dir)
img = fn.decoders.image(data)
flipped = fn.flip(img, horizontal=flip_horizontal, vertical=flip_vertical)
return flipped, img
