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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/01/28 10:46:37 UTC
[GitHub] [tvm] giuseros commented on a change in pull request #7345: pipeline graph patch 1
giuseros commented on a change in pull request #7345:
URL: https://github.com/apache/tvm/pull/7345#discussion_r565990717
##########
File path: python/tvm/relay/analysis/analysis.py
##########
@@ -448,3 +449,71 @@ def get_calibration_data(mod, data):
calib_data[gvar] = value
return calib_data
+
+
+def pipeline_graph(expr, indexs):
+ """Split Graph Into A Group Of Subgraph
+ Parameters
+ ----------
+ expr : tvm.relay.Expr
+ indexs : Array[int]
+
+ Returns
+ -------
+ ret : Array[tvm.relay.IRModule]
+ """
+
+ def run_opt_pass(expr, opt_pass):
+ """Exectue a relay pass"""
+ assert isinstance(opt_pass, tvm.transform.Pass)
+ mod = tvm.IRModule.from_expr(expr)
+ mod = tvm.relay.transform.InferType()(mod)
+ mod = opt_pass(mod)
+ entry = mod["main"]
+ return entry if isinstance(expr, tvm.relay.Function) else entry.body
+
+ def _operator_idx_inc(expr, operator_current_idx):
+ """Increase operator index"""
+ if not isinstance(expr, tvm.relay.expr.Constant):
+ operator_current_idx = operator_current_idx + 1
+
+ return operator_current_idx
+
+ def _recursion(anf, operator_indx, pipeline_mods, indexs):
+ """Do the split work"""
+ if isinstance(anf, tvm.relay.Function):
+ return tvm.relay.Function(
+ anf.params,
+ _recursion(anf.body, operator_indx, pipeline_mods, indexs),
+ anf.ret_type,
+ anf.type_params,
+ anf.attrs,
+ )
+ if isinstance(anf, tvm.relay.expr.Let):
+ value = anf.value
+ operator_indx = _operator_idx_inc(value, operator_indx)
+ if isinstance(value, tvm.relay.expr.Call):
+ if isinstance(value.op, tvm.ir.Op):
+ if indexs and operator_indx == indexs[0]:
+ indexs.pop(0)
+ ann = _recursion(anf.body, operator_indx, pipeline_mods, indexs)
+ ann = run_opt_pass(ann, transform.ToGraphNormalForm())
+ mod = tvm.IRModule.from_expr(ann)
+ pipeline_mods.insert(0, mod)
+ return tvm.relay.expr.Let(anf.var, value, anf.var)
Review comment:
So basically if you have a(b(c(d))) and indexes are [0,1,2,3] you get separate modules for a,b,c,d. Is this correct? If so, would you mind adding some high level comments to help follow the code?
##########
File path: tests/python/relay/test_analysis_pipeline.py
##########
@@ -0,0 +1,69 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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
+#
+# http://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.
+
+import numpy as np
+import tvm
+import tvm.testing
+from tvm import relay
+from tvm.relay import transform
+from tvm.contrib import graph_runtime
+from tvm.relay.analysis import pipeline_graph
+
+
+def run_module(mod, ctx, dname, data):
+ with relay.build_config(opt_level=3):
+ graph, lib, params = relay.build(mod, "llvm")
+
+ m = graph_runtime.create(graph, lib, ctx)
+ m.set_input(dname, data)
+ m.set_input(**params)
+ m.run()
+ output = m.get_output(0).asnumpy()
+ return output
+
+
+def get_network():
+ dshape = (3, 3)
+ mvalue = np.full((1), 4).astype("float32")
+ mmv = relay.Constant(tvm.nd.array(mvalue))
+ mv = relay.Constant(tvm.nd.array(mvalue))
+ mv2 = relay.Constant(tvm.nd.array(mvalue))
+ mv3 = relay.Constant(tvm.nd.array(mvalue))
+ data = relay.var("data", relay.TensorType(dshape, "float32"))
+ net = relay.multiply(data, mv)
+ net = relay.add(net, mv2)
+ net = relay.subtract(net, mv3)
+ net = relay.add(net, mv3)
+ func = relay.Function([data], net)
+ mod = tvm.IRModule.from_expr(func)
+ return mod, dshape
+
+
+mod, dshape = get_network()
+pl = [1, 2]
Review comment:
Should we test also more exotic cases like [0 3 5]? Would this still work (I think so, but better add a test)
##########
File path: python/tvm/relay/analysis/analysis.py
##########
@@ -448,3 +449,71 @@ def get_calibration_data(mod, data):
calib_data[gvar] = value
return calib_data
+
+
+def pipeline_graph(expr, indexs):
+ """Split Graph Into A Group Of Subgraph
+ Parameters
+ ----------
+ expr : tvm.relay.Expr
+ indexs : Array[int]
Review comment:
Minor comment: what about "indices" instead of "indexs"?
##########
File path: python/tvm/relay/analysis/analysis.py
##########
@@ -448,3 +449,71 @@ def get_calibration_data(mod, data):
calib_data[gvar] = value
return calib_data
+
+
+def pipeline_graph(expr, indexs):
+ """Split Graph Into A Group Of Subgraph
+ Parameters
+ ----------
+ expr : tvm.relay.Expr
+ indexs : Array[int]
+
+ Returns
+ -------
+ ret : Array[tvm.relay.IRModule]
+ """
+
+ def run_opt_pass(expr, opt_pass):
+ """Exectue a relay pass"""
+ assert isinstance(opt_pass, tvm.transform.Pass)
+ mod = tvm.IRModule.from_expr(expr)
+ mod = tvm.relay.transform.InferType()(mod)
+ mod = opt_pass(mod)
+ entry = mod["main"]
+ return entry if isinstance(expr, tvm.relay.Function) else entry.body
+
+ def _operator_idx_inc(expr, operator_current_idx):
+ """Increase operator index"""
+ if not isinstance(expr, tvm.relay.expr.Constant):
+ operator_current_idx = operator_current_idx + 1
+
+ return operator_current_idx
+
+ def _recursion(anf, operator_indx, pipeline_mods, indexs):
+ """Do the split work"""
Review comment:
Could we give a more detailed description of what this function is doing?
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