Revert "Revert "MLMBED-3450: Do not convert batched fully connected to conv""
- We have combined estimates for conv and fc, add the fix back
Change-Id: I49a29c716189b37b387df4b46efab5f4e6125994
Signed-off-by: Diqing Zhong <diqing.zhong@arm.com>
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py
index d0d3d7c..13f08f2 100644
--- a/ethosu/vela/graph_optimiser.py
+++ b/ethosu/vela/graph_optimiser.py
@@ -317,7 +317,7 @@
return op
-def convert_batched_fc_to_conv(op, arch, nng):
+def convert_batched_fc_shape(op, arch, nng):
if op.type == Op.FullyConnected:
ifm = op.inputs[0]
ofm = op.outputs[0]
@@ -327,20 +327,6 @@
batching_split = {4: (2, 2), 8: (2, 4), 16: (4, 4)}
h, w = batching_split.get(n, (1, n))
- # Convert to convolution
- op.name += "_conv"
- op.type = Op.Conv2DBias
- op.attrs = {
- "dilation": (1, 1, 1, 1),
- "dilation_h_factor": 1,
- "dilation_w_factor": 1,
- "padding": b"SAME",
- "stride_h": 1,
- "stride_w": 1,
- "strides": (1, 1, 1, 1),
- "is_converted_fc": True,
- }
-
prev_op = ifm.ops[0]
desired_shape = [1, h, w, ifm.shape[-1]]
if len(ifm.consumer_list) == 1 and prev_op is not None and prev_op.type == Op.Reshape:
@@ -381,7 +367,7 @@
else:
op.outputs[0].set_all_shapes(desired_shape)
else:
- # Add rehape op to the output
+ # Add reshape op to the output
op.set_output_tensor(create_reshape_tensor(ofm, desired_shape, False))
return op
@@ -1096,7 +1082,7 @@
convert_conv_to_fc,
convert_softmax,
fixup_fully_connected_input,
- convert_batched_fc_to_conv,
+ convert_batched_fc_shape,
fixup_pack_input,
unfuse_activation_function,
fixup_conv2d_backprop,
diff --git a/ethosu/vela/insert_dma.py b/ethosu/vela/insert_dma.py
index f02039c..fc1e798 100644
--- a/ethosu/vela/insert_dma.py
+++ b/ethosu/vela/insert_dma.py
@@ -77,9 +77,7 @@
):
only_vector_product_consumers = True
for oper in tens.consumers():
- if oper is None or not (
- oper.type.npu_block_type == NpuBlockType.VectorProduct or "is_converted_fc" in oper.attrs
- ):
+ if oper is None or oper.type.npu_block_type != NpuBlockType.VectorProduct:
only_vector_product_consumers = False
break
diff --git a/ethosu/vela/test/test_graph_optimiser.py b/ethosu/vela/test/test_graph_optimiser.py
new file mode 100644
index 0000000..62a1b76
--- /dev/null
+++ b/ethosu/vela/test/test_graph_optimiser.py
@@ -0,0 +1,61 @@
+# Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the License); you may
+# not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an AS IS BASIS, WITHOUT
+# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# Description:
+# Unit tests for graph_optimiser
+import numpy as np
+
+from ethosu.vela.graph_optimiser import convert_batched_fc_shape
+from ethosu.vela.operation import Op
+from ethosu.vela.tensor import create_const_tensor
+from ethosu.vela.tensor import Tensor
+from ethosu.vela.test import testutil
+
+
+def test_convert_batched_fc():
+ """Tests shape conversion of batched fully connected"""
+ shape = [4, 8]
+ ifm = create_const_tensor("test_in", shape, np.uint8, np.zeros(shape))
+ weights = create_const_tensor("weight_in", shape, np.uint8, np.zeros(shape))
+ ofm = Tensor(ifm.shape, np.uint8, "test_out")
+ op = testutil.create_op(Op.FullyConnected, [ifm, weights], ofm)
+ ifm.consumer_list.append(op)
+
+ prev_op = op.clone()
+ conv_op = convert_batched_fc_shape(op, None, None)
+
+ assert conv_op.ifm != prev_op.ifm
+ assert conv_op.ofm != prev_op.ofm
+ assert conv_op.type == Op.FullyConnected
+ assert len(conv_op.ifm.shape) == 4
+ assert conv_op.ifm.shape == conv_op.ofm.shape
+ assert conv_op.ifm.ops[0].type == Op.Reshape
+
+ shape = [1, 8]
+ ifm.shape = shape
+ weights.shape = shape
+ ofm.shape = shape
+ op = testutil.create_op(Op.FullyConnected, [ifm, weights], ofm)
+ ifm.consumer_list.append(op)
+
+ prev_op = op.clone()
+ conv_op = convert_batched_fc_shape(op, None, None)
+
+ assert conv_op.ifm == prev_op.ifm
+ assert conv_op.ofm == prev_op.ofm
+ assert conv_op.type == Op.FullyConnected
+ assert len(conv_op.ifm.shape) == 2
+ assert conv_op.ifm.shape == conv_op.ofm.shape