From 7b4938b44a4b9c2d3d7f0a76e112da8851002ae8 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Tue, 24 May 2022 15:55:54 +0200
Subject: [PATCH] [HLSCustomOp] respect folded shapes in base cppsim I/O
wrappers
---
.../custom_op/fpgadataflow/hlscustomop.py | 28 +++++++++++++++----
1 file changed, 23 insertions(+), 5 deletions(-)
diff --git a/src/finn/custom_op/fpgadataflow/hlscustomop.py b/src/finn/custom_op/fpgadataflow/hlscustomop.py
index ed12d2f1a..030d1834f 100644
--- a/src/finn/custom_op/fpgadataflow/hlscustomop.py
+++ b/src/finn/custom_op/fpgadataflow/hlscustomop.py
@@ -32,6 +32,7 @@ import os
import subprocess
from abc import abstractmethod
+from finn.core.datatype import DataType
from finn.custom_op.base import CustomOp
from finn.util.basic import (
CppBuilder,
@@ -433,10 +434,22 @@ Found no codegen dir for this node, did you run the prepare_cppsim transformatio
# assuming dynamic inputs start from 0
for in_ind in range(count):
current_input_name = node.input[in_ind]
- # make copy before saving array
- input_array = context[current_input_name].copy()
+ input_array = context[current_input_name]
+ if in_ind == 0:
+ expected_inp_shape = self.get_folded_input_shape()
+ idt = self.get_input_datatype()
+ else:
+ expected_inp_shape = self.get_folded_input_shape(in_ind)
+ idt = self.get_input_datatype(in_ind)
+ reshaped_input = input_array.reshape(expected_inp_shape)
+ if idt == DataType["BIPOLAR"]:
+ # store bipolar activations as binary
+ reshaped_input = (reshaped_input + 1) / 2
+ # make copy before saving the array
+ reshaped_input = reshaped_input.copy()
np.save(
- os.path.join(code_gen_dir, "input_{}.npy".format(in_ind)), input_array
+ os.path.join(code_gen_dir, "input_{}.npy".format(in_ind)),
+ reshaped_input,
)
def npy_to_dynamic_output(self, context):
@@ -445,7 +458,8 @@ Found no codegen dir for this node, did you run the prepare_cppsim transformatio
node = self.onnx_node
code_gen_dir = self.get_nodeattr("code_gen_dir_cppsim")
output = np.load("{}/output.npy".format(code_gen_dir))
- context[node.output[0]] = output
+ exp_shape = self.get_normal_output_shape()
+ context[node.output[0]] = output.reshape(exp_shape)
def npy_to_dynamic_outputs(self, context, npy_list):
"""Reads the output from .npy files generated from cppsim and places
@@ -456,7 +470,11 @@ Found no codegen dir for this node, did you run the prepare_cppsim transformatio
code_gen_dir = self.get_nodeattr("code_gen_dir_cppsim")
for i in range(len(npy_list)):
output = np.load("{}/{}".format(code_gen_dir, npy_list[i]))
- context[node.output[i]] = output
+ if i == 0:
+ exp_shape = self.get_normal_output_shape()
+ else:
+ exp_shape = self.get_normal_output_shape(i)
+ context[node.output[i]] = output.reshape(exp_shape)
def exec_precompiled_singlenode_model(self):
"""Executes precompiled executable."""
--
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