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Commit d5292fcb authored by Yaman Umuroglu's avatar Yaman Umuroglu
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[Test] add first sketch for FIFO sizing end2end test

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# Copyright (c) 2022 Xilinx, Inc.
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#
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# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
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# * Neither the name of Xilinx nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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import pkg_resources as pk
import numpy as np
from qonnx.custom_op.registry import getCustomOp
import finn.builder.build_dataflow as build
import finn.builder.build_dataflow_config as build_cfg
from finn.analysis.fpgadataflow.dataflow_performance import dataflow_performance
from finn.transformation.fpgadataflow.derive_characteristic import DeriveCharacteristic
from finn.transformation.fpgadataflow.prepare_rtlsim import PrepareRTLSim
from finn.util.basic import make_build_dir
def custom_step_fifosize(model, cfg):
# TODO convert to NodeLocalTransformation
def accumulate_char_fxn(chrc):
p = len(chrc)
ret = []
for t in range(2 * p):
if t == 0:
ret.append(chrc[0])
else:
ret.append(ret[-1] + chrc[t % p])
return ret
# TODO handle chrc for input and output nodes
all_act_tensors = [x.name for x in model.graph.value_info]
for tensor_nm in all_act_tensors:
# generate accumulated characteristic functions
prod = getCustomOp(model.find_producer(tensor_nm))
prod_chrc = prod.get_nodeattr("io_characteristic")
prod_chrc = np.asarray(prod_chrc, dtype=np.uint8).reshape(2, -1)[1]
prod_chrc = accumulate_char_fxn(prod_chrc)
cons = getCustomOp(model.find_consumer(tensor_nm))
cons_chrc = cons.get_nodeattr("io_characteristic")
cons_chrc = np.asarray(cons_chrc, dtype=np.uint8).reshape(2, -1)[0]
cons_chrc = accumulate_char_fxn(cons_chrc)
# TODO find minimum phase shift
for node in model.graph.node:
inst = getCustomOp(node)
chrc = inst.get_nodeattr("io_characteristic")
chrc = np.asarray(chrc, dtype=np.uint8).reshape(2, -1)
return model
def custom_step_fifocharacterize(model, cfg):
model = model.transform(PrepareRTLSim())
period = model.analysis(dataflow_performance)["max_cycles"] + 10
model = model.transform(DeriveCharacteristic(period))
return model
def test_end2end_fifosizing():
chkpt_name = pk.resource_filename("finn.qnn-data", "build_dataflow/model.onnx")
tmp_output_dir = make_build_dir("build_fifosizing_")
# tmp_output_dir = "/tmp/finn_dev_maltanar/build_fifosizing_5mt0o6s_"
steps = build_cfg.default_build_dataflow_steps
steps = steps[:10]
steps.append(custom_step_fifocharacterize)
# steps.append(custom_step_fifosize)
cfg = build_cfg.DataflowBuildConfig(
output_dir=tmp_output_dir,
auto_fifo_depths=False,
target_fps=10000,
synth_clk_period_ns=10.0,
board="Pynq-Z1",
shell_flow_type=build_cfg.ShellFlowType.VIVADO_ZYNQ,
generate_outputs=[],
steps=steps,
default_mem_mode=build_cfg.ComputeEngineMemMode.CONST,
start_step="custom_step_fifocharacterize",
)
build.build_dataflow_cfg(chkpt_name, cfg)
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