Revert "MLMBED-3450: Do not convert batched fully connected to conv"2.0.0.rc2

This reverts commit 15a8e803844b286fe9533e1cf703c76a77b090a8.

Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: I64169443f473c9ba42551281ad6ac4b45856f420

2 files changed, 16 insertions, 64 deletions

diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py
index 7401927..5889905 100644
--- a/ethosu/vela/graph_optimiser.py
+++ b/ethosu/vela/graph_optimiser.py
@@ -317,7 +317,7 @@ def fixup_fully_connected_input(op, arch, nng):
     return op
 
 
-def convert_batched_fc_shape(op, arch, nng):
+def convert_batched_fc_to_conv(op, arch, nng):
     if op.type == Op.FullyConnected:
         ifm = op.inputs[0]
         ofm = op.outputs[0]
@@ -327,6 +327,19 @@ def convert_batched_fc_shape(op, arch, nng):
             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),
+            }
+
             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:
@@ -367,7 +380,7 @@ def convert_batched_fc_shape(op, arch, nng):
                 else:
                     op.outputs[0].set_all_shapes(desired_shape)
             else:
-                # Add reshape op to the output
+                # Add rehape op to the output
                 op.set_output_tensor(create_reshape_tensor(ofm, desired_shape, False))
     return op
 
@@ -1082,7 +1095,7 @@ def optimise_graph_a(nng, arch, verbose_graph=False):
         convert_conv_to_fc,
         convert_softmax,
         fixup_fully_connected_input,
-        convert_batched_fc_shape,
+        convert_batched_fc_to_conv,
         fixup_pack_input,
         unfuse_activation_function,
         fixup_conv2d_backprop,
diff --git a/ethosu/vela/test/test_graph_optimiser.py b/ethosu/vela/test/test_graph_optimiser.py
deleted file mode 100644
index 62a1b76..0000000
--- a/ethosu/vela/test/test_graph_optimiser.py
+++ /dev/null
@@ -1,61 +0,0 @@
-# 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