def pop(self):
# Wait for finish signal
out_slot = self.out_index % self.n_streams
self.fpgaRT.get_result(out_slot)
# Read output
response = self.output_buffers[out_slot]
fcOutput = np.empty((response["fc1000/Reshape_output"].shape[0], 1000),
dtype=np.float32,
order='C')
xdnn.computeFC(self.fcWeight, self.fcBias,
response["fc1000/Reshape_output"], fcOutput)
response = request_wrapper.dictToProto(
{"fc1000/Reshape_output": fcOutput})
self.out_index += 1
return response
def imagenet_request_generator(file_name, n):
try:
i = 0
data = []
for image in imagenet_image_generator(file_name, n):
data.append(image)
i += 1
if i == BATCH_SIZE:
request = {INPUT_NODE_NAME: np.array(data, dtype=np.float32)}
yield request_wrapper.dictToProto(request)
i = 0
data = []
except Exception as e:
import traceback
traceback.print_exc()
raise e
def empty_image_generator(n):
'''
Generate empty images
n: number of images
'''
for _ in range(n // BATCH_SIZE):
if STACK:
request = {
INPUT_NODE_NAME: np.zeros((BATCH_SIZE, 224, 224),
dtype=np.float32)
}
else:
request = {
INPUT_NODE_NAME:
np.zeros((BATCH_SIZE, 3, 224, 224), dtype=np.float32)
}
request = request_wrapper.dictToProto(request)
yield request