From c4a6ccea5a4cdf85baee5b0a988a5305149d9b57 Mon Sep 17 00:00:00 2001
From: Hendrik Borras <hendrikborras@web.de>
Date: Wed, 13 Oct 2021 12:09:20 +0100
Subject: [PATCH] Moved RemoveIdentityOps transformation from FINN to
finn-base.
---
docker/Dockerfile.finn | 2 +-
.../transformation/streamline/__init__.py | 2 +-
src/finn/transformation/streamline/remove.py | 92 ------------------
tests/end2end/test_end2end_mobilenet_v1.py | 2 +-
.../streamline/test_remove_identity_ops.py | 95 -------------------
5 files changed, 3 insertions(+), 190 deletions(-)
delete mode 100644 src/finn/transformation/streamline/remove.py
delete mode 100644 tests/transformation/streamline/test_remove_identity_ops.py
diff --git a/docker/Dockerfile.finn b/docker/Dockerfile.finn
index 5a7a90ec4..1276a94a8 100644
--- a/docker/Dockerfile.finn
+++ b/docker/Dockerfile.finn
@@ -86,7 +86,7 @@ RUN pip install -e git+https://github.com/fbcotter/dataset_loading.git@0.0.4#egg
# git-based Python repo dependencies
# these are installed in editable mode for easier co-development
-ARG FINN_BASE_COMMIT="17687a6a3371936147ceb4ed0d49f985a7ea9fde"
+ARG FINN_BASE_COMMIT="7f13a67ba27c4f2c979bcbca26f49a5409b4b433"
ARG QONNX_COMMIT="02b15f56d199576cefe9aff672d5e009349e402a"
ARG FINN_EXP_COMMIT="f82c0d9868bb88ea045dfadb28508d327d287221"
ARG BREVITAS_COMMIT="462f86cdc60f9915baf13afd1676fb21da44c2ee"
diff --git a/src/finn/transformation/streamline/__init__.py b/src/finn/transformation/streamline/__init__.py
index ea5475716..d0ec26a4d 100644
--- a/src/finn/transformation/streamline/__init__.py
+++ b/src/finn/transformation/streamline/__init__.py
@@ -39,6 +39,7 @@ from finn.transformation.general import (
GiveUniqueNodeNames,
)
from finn.transformation.infer_datatypes import InferDataTypes
+from finn.transformation.remove import RemoveIdentityOps
from finn.transformation.streamline.absorb import (
Absorb1BitMulIntoConv,
Absorb1BitMulIntoMatMul,
@@ -51,7 +52,6 @@ from finn.transformation.streamline.collapse_repeated import (
CollapseRepeatedAdd,
CollapseRepeatedMul,
)
-from finn.transformation.streamline.remove import RemoveIdentityOps
from finn.transformation.streamline.reorder import (
MoveAddPastConv,
MoveAddPastMul,
diff --git a/src/finn/transformation/streamline/remove.py b/src/finn/transformation/streamline/remove.py
deleted file mode 100644
index 27e420a79..000000000
--- a/src/finn/transformation/streamline/remove.py
+++ /dev/null
@@ -1,92 +0,0 @@
-# Copyright (c) 2020, Xilinx
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions are met:
-#
-# * Redistributions of source code must retain the above copyright notice, this
-# list of conditions and the following disclaimer.
-#
-# * Redistributions in binary form must reproduce the above copyright notice,
-# this list of conditions and the following disclaimer in the documentation
-# and/or other materials provided with the distribution.
-#
-# * Neither the name of FINN 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
-# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
-# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
-# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
-# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
-# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-
-import numpy as np
-
-from finn.transformation.base import Transformation
-from finn.transformation.infer_shapes import InferShapes
-
-
-def _remove_node_and_rewire(model, node):
- producer = model.find_producer(node.input[0])
- if producer is not None:
- # wire output tensor to
- # output of producer node
- producer.output[0] = node.output[0]
- else:
- # node is first in graph
- consumer = model.find_consumer(node.output[0])
- assert consumer is not None, "Whole graph is identity"
- assert consumer.input[0] == node.output[0]
- # rewire consumer's input directly to graph input
- consumer.input[0] = node.input[0]
- # remove node
- model.graph.node.remove(node)
-
-
-class RemoveIdentityOps(Transformation):
- """Remove identity ops like Add/Sub with zero or Mul/Div with one. A tolerance
- value (defaults to 1e-05) can be specified during init for the comparison
- to zero/one."""
-
- def __init__(self, atol=1e-05):
- super().__init__()
- self.atol = atol
-
- def apply(self, model):
- graph = model.graph
- node_ind = 0
- graph_modified = False
- for n in graph.node:
- node_ind += 1
- if (
- n.op_type in ["Add", "Sub"]
- and not model.is_fork_node(n)
- and not model.is_join_node(n)
- ):
- A = model.get_initializer(n.input[1])
- if (
- A is not None
- and np.isclose(A, np.zeros_like(A), atol=self.atol).all()
- ):
- _remove_node_and_rewire(model, n)
-
- elif (
- n.op_type in ["Mul", "Div"]
- and not model.is_fork_node(n)
- and not model.is_join_node(n)
- ):
- A = model.get_initializer(n.input[1])
- if (
- A is not None
- and np.isclose(A, np.ones_like(A), atol=self.atol).all()
- ):
- _remove_node_and_rewire(model, n)
- model = model.transform(InferShapes())
- return (model, graph_modified)
diff --git a/tests/end2end/test_end2end_mobilenet_v1.py b/tests/end2end/test_end2end_mobilenet_v1.py
index 760c77ea4..6af5019d7 100644
--- a/tests/end2end/test_end2end_mobilenet_v1.py
+++ b/tests/end2end/test_end2end_mobilenet_v1.py
@@ -62,9 +62,9 @@ from finn.transformation.infer_shapes import InferShapes
from finn.transformation.insert_topk import InsertTopK
from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
from finn.transformation.merge_onnx_models import MergeONNXModels
+from finn.transformation.remove import RemoveIdentityOps
from finn.transformation.streamline import Streamline
from finn.transformation.streamline.collapse_repeated import CollapseRepeatedMul
-from finn.transformation.streamline.remove import RemoveIdentityOps
from finn.transformation.streamline.round_thresholds import RoundAndClipThresholds
from finn.util.basic import alveo_default_platform, alveo_part_map
from finn.util.pytorch import NormalizePreProc
diff --git a/tests/transformation/streamline/test_remove_identity_ops.py b/tests/transformation/streamline/test_remove_identity_ops.py
deleted file mode 100644
index ad7c20fb5..000000000
--- a/tests/transformation/streamline/test_remove_identity_ops.py
+++ /dev/null
@@ -1,95 +0,0 @@
-import pytest
-
-import numpy as np
-from onnx import TensorProto, helper
-
-import finn.core.onnx_exec as oxe
-from finn.core.datatype import DataType
-from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.infer_datatypes import InferDataTypes
-from finn.transformation.infer_shapes import InferShapes
-from finn.transformation.streamline.remove import RemoveIdentityOps
-from finn.util.basic import gen_finn_dt_tensor
-
-
-def insert_identity_op(model, op, as_first_node, approx):
- if approx:
- zero_val = 0.000001
- one_val = 0.999999
- else:
- zero_val = 0.0
- one_val = 1.0
- if op in ["Add", "Sub"]:
- val = np.asarray([zero_val], dtype=np.float32)
- elif op in ["Mul", "Div"]:
- val = np.asarray([one_val], dtype=np.float32)
- else:
- return
-
- graph = model.graph
- if as_first_node:
- identity_node = helper.make_node(op, ["inp", "value"], ["ident_out"])
- graph.node.insert(0, identity_node)
- graph.node[1].input[0] = "ident_out"
- else:
- identity_node = helper.make_node(op, ["div_out", "value"], ["ident_out"])
- graph.node.insert(3, identity_node)
- graph.node[-1].input[0] = "ident_out"
- model.set_initializer("value", val)
-
- return model
-
-
-# identity operations to be inserted
-@pytest.mark.parametrize("op", ["Add", "Sub", "Mul", "Div"])
-@pytest.mark.parametrize("approx", [False, True])
-@pytest.mark.parametrize("as_first_node", [False, True])
-def test_remove_identity_ops(op, as_first_node, approx):
-
- # set up onnx model
- inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, 4, 1, 1])
- mul = helper.make_tensor_value_info("mul", TensorProto.FLOAT, [])
- shape = helper.make_tensor_value_info("shape", TensorProto.FLOAT, [2])
- div = helper.make_tensor_value_info("div", TensorProto.FLOAT, [])
- matmul = helper.make_tensor_value_info("matmul", TensorProto.FLOAT, [4, 2])
- outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, 2])
-
- mul_node = helper.make_node("Mul", ["inp", "mul"], ["mul_out"])
- reshape_node = helper.make_node("Reshape", ["mul_out", "shape"], ["reshape_out"])
- div_node = helper.make_node("Div", ["reshape_out", "div"], ["div_out"])
- matmul_node = helper.make_node("MatMul", ["div_out", "matmul"], ["outp"])
-
- graph = helper.make_graph(
- nodes=[mul_node, reshape_node, div_node, matmul_node],
- name="identity-graph",
- inputs=[inp],
- outputs=[outp],
- value_info=[mul, shape, div, matmul],
- )
-
- model = helper.make_model(graph, producer_name="mulpastconv-model")
- model = ModelWrapper(model)
- inp_values = gen_finn_dt_tensor(DataType.INT2, [1, 4, 1, 1])
- mul_values = np.random.uniform(low=0.1, high=0.99, size=(1)).astype(np.float32)
- shape_values = np.asarray([1, -1], dtype=np.int64)
- div_values = np.random.uniform(low=0.1, high=0.99, size=(1)).astype(np.float32)
- matmul_values = gen_finn_dt_tensor(DataType.INT2, [4, 2])
- model.set_initializer("mul", mul_values)
- model.set_initializer("shape", shape_values)
- model.set_initializer("div", div_values)
- model.set_initializer("matmul", matmul_values)
- insert_identity_op(model, op, as_first_node, approx)
- model = model.transform(InferShapes())
- model = model.transform(InferDataTypes())
- idict = {"inp": inp_values}
- odict = oxe.execute_onnx(model, idict)
- out_before = odict["outp"]
- num_of_nodes_before = len(model.graph.node)
-
- model = model.transform(RemoveIdentityOps())
- num_of_nodes_after = len(model.graph.node)
- assert num_of_nodes_before - 1 == num_of_nodes_after
-
- odict = oxe.execute_onnx(model, idict)
- out_after = odict["outp"]
- assert np.isclose(out_before, out_after, atol=1e-3).all()
--
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