diff --git a/src/finn/transformation/fpgadataflow/templates.py b/src/finn/transformation/fpgadataflow/templates.py
index d4d32b84e0f81345a630d35d10906dd13a280662..55ecb57decd2ac4fa08331b5ebbcb7fd2f0cd5c6 100644
--- a/src/finn/transformation/fpgadataflow/templates.py
+++ b/src/finn/transformation/fpgadataflow/templates.py
@@ -104,7 +104,8 @@ from finn.core.datatype import DataType
class FINNAccelDriver():
def __init__(self, N, bitfile):
- # batchsize
+ \"\"\"Instantiate the FINN accelerator driver.
+ Gets batchsize (N) as integer and path to bitfile as string.\"\"\"
self.N = N
# input FINN DataType
self.idt = $INPUT_FINN_DATATYPE$
@@ -115,8 +116,8 @@ class FINNAccelDriver():
self.oshape_normal = $OUTPUT_SHAPE_NORMAL$
self.ishape_folded = $INPUT_SHAPE_FOLDED$
self.oshape_folded = $OUTPUT_SHAPE_FOLDED$
- self.ishape_packed = $INPUT_SHAPE_PACKED$
- self.oshape_packed = $OUTPUT_SHAPE_PACKED$
+ self.ishape_packed = $INPUT_SHAPE_PACKED$ # datatype np.uint8
+ self.oshape_packed = $OUTPUT_SHAPE_PACKED$ # datatype np.uint8
# load bitfile and set up accelerator
self.ol = Overlay(bitfile)
self.dma = self.ol.axi_dma_0
@@ -134,40 +135,45 @@ class FINNAccelDriver():
self.obuf_packed_device = allocate(shape=self.oshape_packed, dtype=np.uint8)
def fold_input(self, ibuf_normal):
- # reshape input in desired shape
- N = self.N
+ \"\"\"Reshapes input in desired shape.
+ Gets input data (ibuf_normal), checks if data is in expected normal shape.
+ Returns folded input.\"\"\"
+ # ensure that shape is as expected
+ assert ibuf_normal.shape == self.ishape_normal
# convert to folded form
ibuf_folded = ibuf_normal.reshape(self.ishape_folded)
return ibuf_folded
def pack_input(self, ibuf_folded):
- # pack the input buffer, reversing both SIMD dim and endianness
- N = self.N
+ \"\"\"Packs folded input and reverses both SIMD dim and endianness.
+ Gets input data in folded shape and returns packed input data.\"\"\"
ibuf_packed = finnpy_to_packed_bytearray(
ibuf_folded, self.idt, reverse_endian=True, reverse_inner=True
)
return ibuf_packed
def unpack_output(self, obuf_packed):
- # unpack the packed output buffer from accelerator
- N = self.N
+ \"\"\"Unpacks the packed output buffer from accelerator.
+ Gets packed output and returns output data in folded shape.\"\"\"
obuf_folded = packed_bytearray_to_finnpy(
obuf_packed, self.odt, self.oshape_folded, reverse_endian=True, reverse_inner=True
)
return obuf_folded
def unfold_output(self, obuf_folded):
- # unfold to normal shape
- N = self.N
+ \"\"\"Unfolds output data to normal shape.
+ Gets folded output data and returns output data in normal shape.\"\"\"
obuf_normal = obuf_folded.reshape(self.oshape_normal)
return obuf_normal
- def copy_data_to_pynqbuffer(self, data):
- # copy data to PYNQ buffer
+ def copy_input_data_to_device(self, data):
+ \"\"\"Copies given input data to PYNQ buffer.\"\"\"
np.copyto(self.ibuf_packed_device, data)
- def execute_accel(self):
- # set up the DMA and wait until all transfers complete
+ def execute(self):
+ \"\"\"Executes accelerator by setting up the DMA and
+ waiting until all transfers complete. Uses only member variables and
+ returns nothing.\"\"\"
dma = self.dma
dma.sendchannel.transfer(self.ibuf_packed_device)
dma.recvchannel.transfer(self.obuf_packed_device)
@@ -177,8 +183,8 @@ class FINNAccelDriver():
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Set exec mode, batchsize N, bitfile name, inputfile name and outputfile name')
- parser.add_argument('--exec_mode', help='Please select functional verification ("remote_pynq") or throughput test ("throughput_test")')
- parser.add_argument('--batchsize', help='number of samples for inference', type=int)
+ parser.add_argument('--exec_mode', help='Please select functional verification ("execute") or throughput test ("throughput_test")', default="execute")
+ parser.add_argument('--batchsize', help='number of samples for inference', type=int, default=1)
parser.add_argument('--bitfile', help='name of bitfile (i.e. "resizer.bit")', default="resizer.bit")
parser.add_argument('--inputfile', help='name of input npy file (i.e. "input.npy")', default="input.npy")
parser.add_argument('--outputfile', help='name of output npy file (i.e. "output.npy")', default="output.npy")
@@ -195,14 +201,12 @@ if __name__ == "__main__":
# for the remote execution the data from the input npy file has to be loaded,
# packed and copied to the PYNQ buffer
- if exec_mode == "remote_pynq":
+ if exec_mode == "execute":
# load desired input .npy file
ibuf_normal = np.load(inputfile)
- # ensure that shape is as expected
- assert ibuf_normal.shape == finnDriver.ishape_normal
ibuf_folded = finnDriver.fold_input(ibuf_normal)
ibuf_packed = finnDriver.pack_input(ibuf_folded)
- finnDriver.copy_data_to_pynqbuffer(ibuf_packed)
+ finnDriver.copy_input_data_to_device(ibuf_packed)
elif exec_mode != "throughput_test":
raise Exception("Exec mode has to be set to remote_pynq or throughput_test")
@@ -214,7 +218,7 @@ if __name__ == "__main__":
res={}
# execute accelerator
- finnDriver.execute_accel()
+ finnDriver.execute()
# measure run time and fill dictionary with results of the throughput test
if exec_mode == "throughput_test":
@@ -228,7 +232,7 @@ if __name__ == "__main__":
file.write(str(res))
file.close()
- # if remote execution is selected unpack, unfold and save output to output npy file
+ # if execution is selected unpack, unfold and save output to output npy file
else:
obuf_folded = finnDriver.unpack_output(finnDriver.obuf_packed_device)
obuf_normal = finnDriver.unfold_output(obuf_folded)