From 1ee4b9446c4c782ff200db75d14c1260b8ab3fee Mon Sep 17 00:00:00 2001
From: Tobi-Alonso <tobi.alonso@gmail.com>
Date: Tue, 7 Jul 2020 17:14:12 +0100
Subject: [PATCH] [HLSCustomOp] Fix inferShapes for InferDuplicateStreamsLayer
---
.../fpgadataflow/duplicatestreams_batch.py | 17 ++++++-----------
1 file changed, 6 insertions(+), 11 deletions(-)
diff --git a/src/finn/custom_op/fpgadataflow/duplicatestreams_batch.py b/src/finn/custom_op/fpgadataflow/duplicatestreams_batch.py
index 54051af5e..8143b9c55 100644
--- a/src/finn/custom_op/fpgadataflow/duplicatestreams_batch.py
+++ b/src/finn/custom_op/fpgadataflow/duplicatestreams_batch.py
@@ -32,7 +32,7 @@ import numpy as np
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow import HLSCustomOp
-from onnx import TensorProto, helper
+from onnx import helper
from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
@@ -80,24 +80,19 @@ class DuplicateStreams_Batch(HLSCustomOp):
def make_shape_compatible_op(self, model):
exp_ishape = self.get_normal_input_shape()
- oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpected input shape."
- # implement tensor with correct shape
- values = np.random.randn(*oshape).astype(np.float32)
- split_input = np.concatenate((values, values), axis=0)
return helper.make_node(
- "Split",
- inputs=[split_input],
- outputs=[self.onnx_node.output[0], self.onnx_node.output[0]],
- value=helper.make_tensor(
- name="const_tensor", data_type=TensorProto.FLOAT, axis=0
- ),
+ "Dropout",
+ inputs=[self.onnx_node.input[0]],
+ outputs=[self.onnx_node.output[0], self.onnx_node.output[1]],
+ axis=0,
)
def infer_node_datatype(self, model):
odt = self.get_output_datatype()
model.set_tensor_datatype(self.onnx_node.output[0], odt)
+ model.set_tensor_datatype(self.onnx_node.output[1], odt)
def verify_node(self):
info_messages = []
--
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