[GitHub] [incubator-tvm] yongfeng-nv commented on a change in pull request #4651: Tensor Expression Debug Display (TEDD)
yongfeng-nv commented on a change in pull request #4651: Tensor Expression
Debug Display (TEDD)
URL: https://github.com/apache/incubator-tvm/pull/4651#discussion_r365324499
##
File path: python/tvm/contrib/tedd.py
##
@@ -0,0 +1,506 @@
+# 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.
+"""Tensor Expression Debug Display (TEDD), visualizing Tensor Expression"""
+import html
+from graphviz import Digraph
+from graphviz import Source
+from IPython.display import display
+from IPython.display import SVG
+import tvm
+
+TVMDD_TABLE_BODY_WIDTH = 30
+# Must match enum IterVarType defined in include/tvm/expr.h
+ITERVAR_TYPE_STRING_MAP = {
+0: ('kDataPar', '#FF'),
+1: ('kThreadIndex', '#2980B9'),
+2: ('kCommReduce', '#FAD7A0'),
+3: ('kOrdered', '#D35400'),
+4: ('kOpaque', '#ABB2B9'),
+5: ('kUnrolled', '#D2B4DE'),
+6: ('kVectorized', '#AED6F1'),
+7: ('kParallelized', '#F5B7B1'),
+8: ('kTensorized', '#A9DFBF'),
+}
+
+
+def get_or_create_dot_id(obj, prefix="", assert_on_missing=False):
+"""If obj's ID has been registered, return it.
+ If not, either assert or create a unique and legal ID, register and
+ return it, according to assert_on_missing.
+ ID must be a unique and legal Dotty ID.
+
+Parameters
+--
+obj : objet
+Serve as the key to the ID.
+
+prefix : string
+Prefix to attach to the ID. Usually use obj's non-unique
+name as prefix.
+
+assert_on_missing : bool
+Asserts or not if object doesn't have a registered ID.
+"""
+prefix = prefix.replace('.', '_')
+if not hasattr(get_or_create_dot_id, "obj_id_dict"):
+get_or_create_dot_id.obj_id_dict = {}
+if obj not in get_or_create_dot_id.obj_id_dict:
+if assert_on_missing:
+assert False, 'dot_id ' + str(obj) + ' has not been registered.'
+else:
+get_or_create_dot_id.obj_id_dict[obj] = prefix + hex(id(obj))
+return get_or_create_dot_id.obj_id_dict[obj]
+
+
+def get_port_id(is_input, index):
+return 'I_' + str(index) if is_input else 'O_' + str(index)
+
+
+def get_itervar_type_info(iter_type):
+assert iter_type < len(
+ITERVAR_TYPE_STRING_MAP), 'Unknown IterVar type: ' + str(iter_type)
+return ITERVAR_TYPE_STRING_MAP[iter_type]
+
+
+def get_itervar_label_color(itervar, iv_type):
+type_info = get_itervar_type_info(iv_type)
+return str(itervar.var) + '(' + type_info[0] + ')', type_info[1]
+
+
+def linebrk(s, n):
+""" Break input string s with for every n charactors."""
+result = ''
+j = 0
+for i, c in enumerate(s):
+if j == n and i != len(s) - 1:
+result = result + '\n'
+j = 0
+j = j + 1
+result = result + c
+result = html.escape(str(result), quote=True)
+result = result.replace('\n', '')
+return result
+
+
+def create_graph(name="", rankdir='BT'):
+graph = Digraph(name=name)
+graph.graph_attr['rankdir'] = rankdir
+return graph
+
+
+def itervar_label(itervar, index, index_color, label):
+return '' + str(
+index
+) + '' + label + ''
+
+
+def stage_label(stage):
+return stage.op.name + 'Scope: ' + stage.scope
+
+
+def legend_label():
+label = '<'
+for iter_type in ITERVAR_TYPE_STRING_MAP:
+name, color = ITERVAR_TYPE_STRING_MAP[iter_type]
+label += '' \
++ '' + name + ''
+label += '>'
+return label
+
+
+def legend_dot(g):
+with g.subgraph(name='cluster_legend') as subgraph:
+subgraph.attr(label='Legend')
+label = legend_label()
+subgraph.node('legend', label, shape='none', margin='0')
+
+
+def dump_graph(dot_string,
+ showsvg=True,
+ dotfilepath='',
+ outputdotstring=False):
+"""Output dot_string in various formats."""
+if dotfilepath:
+try:
+dot_file = open(dotfilepath, "w+")
+dot_file.write(dot_string)
+dot_file.close()
+except IOError:
+print('Cannot open file: ' + dotfilepath)
+if showsvg:
+src = Source(dot_string)
+
[GitHub] [incubator-tvm] yongfeng-nv commented on a change in pull request #4651: Tensor Expression Debug Display (TEDD)
yongfeng-nv commented on a change in pull request #4651: Tensor Expression
Debug Display (TEDD)
URL: https://github.com/apache/incubator-tvm/pull/4651#discussion_r365031269
##
File path: python/tvm/contrib/tedd.py
##
@@ -0,0 +1,506 @@
+# 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.
+"""Tensor Expression Debug Display (TEDD), visualizing Tensor Expression"""
+import html
+from graphviz import Digraph
+from graphviz import Source
+from IPython.display import display
+from IPython.display import SVG
+import tvm
+
+TVMDD_TABLE_BODY_WIDTH = 30
+# Must match enum IterVarType defined in include/tvm/expr.h
+ITERVAR_TYPE_STRING_MAP = {
+0: ('kDataPar', '#FF'),
+1: ('kThreadIndex', '#2980B9'),
+2: ('kCommReduce', '#FAD7A0'),
+3: ('kOrdered', '#D35400'),
+4: ('kOpaque', '#ABB2B9'),
+5: ('kUnrolled', '#D2B4DE'),
+6: ('kVectorized', '#AED6F1'),
+7: ('kParallelized', '#F5B7B1'),
+8: ('kTensorized', '#A9DFBF'),
+}
+
+
+def get_or_create_dot_id(obj, prefix="", assert_on_missing=False):
+"""If obj's ID has been registered, return it.
+ If not, either assert or create a unique and legal ID, register and
+ return it, according to assert_on_missing.
+ ID must be a unique and legal Dotty ID.
+
+Parameters
+--
+obj : objet
+Serve as the key to the ID.
+
+prefix : string
+Prefix to attach to the ID. Usually use obj's non-unique
+name as prefix.
+
+assert_on_missing : bool
+Asserts or not if object doesn't have a registered ID.
+"""
+prefix = prefix.replace('.', '_')
+if not hasattr(get_or_create_dot_id, "obj_id_dict"):
+get_or_create_dot_id.obj_id_dict = {}
+if obj not in get_or_create_dot_id.obj_id_dict:
+if assert_on_missing:
+assert False, 'dot_id ' + str(obj) + ' has not been registered.'
+else:
+get_or_create_dot_id.obj_id_dict[obj] = prefix + hex(id(obj))
+return get_or_create_dot_id.obj_id_dict[obj]
+
+
+def get_port_id(is_input, index):
+return 'I_' + str(index) if is_input else 'O_' + str(index)
+
+
+def get_itervar_type_info(iter_type):
+assert iter_type < len(
+ITERVAR_TYPE_STRING_MAP), 'Unknown IterVar type: ' + str(iter_type)
+return ITERVAR_TYPE_STRING_MAP[iter_type]
+
+
+def get_itervar_label_color(itervar, iv_type):
+type_info = get_itervar_type_info(iv_type)
+return str(itervar.var) + '(' + type_info[0] + ')', type_info[1]
+
+
+def linebrk(s, n):
+""" Break input string s with for every n charactors."""
+result = ''
+j = 0
+for i, c in enumerate(s):
+if j == n and i != len(s) - 1:
+result = result + '\n'
+j = 0
+j = j + 1
+result = result + c
+result = html.escape(str(result), quote=True)
+result = result.replace('\n', '')
+return result
+
+
+def create_graph(name="", rankdir='BT'):
+graph = Digraph(name=name)
+graph.graph_attr['rankdir'] = rankdir
+return graph
+
+
+def itervar_label(itervar, index, index_color, label):
+return '' + str(
+index
+) + '' + label + ''
+
+
+def stage_label(stage):
+return stage.op.name + 'Scope: ' + stage.scope
+
+
+def legend_label():
+label = '<'
+for iter_type in ITERVAR_TYPE_STRING_MAP:
+name, color = ITERVAR_TYPE_STRING_MAP[iter_type]
+label += '' \
++ '' + name + ''
+label += '>'
+return label
+
+
+def legend_dot(g):
+with g.subgraph(name='cluster_legend') as subgraph:
+subgraph.attr(label='Legend')
+label = legend_label()
+subgraph.node('legend', label, shape='none', margin='0')
+
+
+def dump_graph(dot_string,
+ showsvg=True,
+ dotfilepath='',
+ outputdotstring=False):
+"""Output dot_string in various formats."""
+if dotfilepath:
+try:
+dot_file = open(dotfilepath, "w+")
+dot_file.write(dot_string)
+dot_file.close()
+except IOError:
+print('Cannot open file: ' + dotfilepath)
+if showsvg:
+src = Source(dot_string)
+
[GitHub] [incubator-tvm] yongfeng-nv commented on a change in pull request #4651: Tensor Expression Debug Display (TEDD)
yongfeng-nv commented on a change in pull request #4651: Tensor Expression
Debug Display (TEDD)
URL: https://github.com/apache/incubator-tvm/pull/4651#discussion_r365005585
##
File path: python/tvm/contrib/tedd.py
##
@@ -0,0 +1,506 @@
+# 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.
+"""Tensor Expression Debug Display (TEDD), visualizing Tensor Expression"""
+import html
+from graphviz import Digraph
+from graphviz import Source
+from IPython.display import display
+from IPython.display import SVG
+import tvm
+
+TVMDD_TABLE_BODY_WIDTH = 30
+# Must match enum IterVarType defined in include/tvm/expr.h
+ITERVAR_TYPE_STRING_MAP = {
+0: ('kDataPar', '#FF'),
+1: ('kThreadIndex', '#2980B9'),
+2: ('kCommReduce', '#FAD7A0'),
+3: ('kOrdered', '#D35400'),
+4: ('kOpaque', '#ABB2B9'),
+5: ('kUnrolled', '#D2B4DE'),
+6: ('kVectorized', '#AED6F1'),
+7: ('kParallelized', '#F5B7B1'),
+8: ('kTensorized', '#A9DFBF'),
+}
+
+
+def get_or_create_dot_id(obj, prefix="", assert_on_missing=False):
+"""If obj's ID has been registered, return it.
+ If not, either assert or create a unique and legal ID, register and
+ return it, according to assert_on_missing.
+ ID must be a unique and legal Dotty ID.
+
+Parameters
+--
+obj : objet
+Serve as the key to the ID.
+
+prefix : string
+Prefix to attach to the ID. Usually use obj's non-unique
+name as prefix.
+
+assert_on_missing : bool
+Asserts or not if object doesn't have a registered ID.
+"""
+prefix = prefix.replace('.', '_')
+if not hasattr(get_or_create_dot_id, "obj_id_dict"):
+get_or_create_dot_id.obj_id_dict = {}
+if obj not in get_or_create_dot_id.obj_id_dict:
+if assert_on_missing:
+assert False, 'dot_id ' + str(obj) + ' has not been registered.'
+else:
+get_or_create_dot_id.obj_id_dict[obj] = prefix + hex(id(obj))
+return get_or_create_dot_id.obj_id_dict[obj]
+
+
+def get_port_id(is_input, index):
+return 'I_' + str(index) if is_input else 'O_' + str(index)
+
+
+def get_itervar_type_info(iter_type):
+assert iter_type < len(
+ITERVAR_TYPE_STRING_MAP), 'Unknown IterVar type: ' + str(iter_type)
+return ITERVAR_TYPE_STRING_MAP[iter_type]
+
+
+def get_itervar_label_color(itervar, iv_type):
+type_info = get_itervar_type_info(iv_type)
+return str(itervar.var) + '(' + type_info[0] + ')', type_info[1]
+
+
+def linebrk(s, n):
+""" Break input string s with for every n charactors."""
+result = ''
+j = 0
+for i, c in enumerate(s):
+if j == n and i != len(s) - 1:
+result = result + '\n'
+j = 0
+j = j + 1
+result = result + c
+result = html.escape(str(result), quote=True)
+result = result.replace('\n', '')
+return result
+
+
+def create_graph(name="", rankdir='BT'):
+graph = Digraph(name=name)
+graph.graph_attr['rankdir'] = rankdir
+return graph
+
+
+def itervar_label(itervar, index, index_color, label):
+return '' + str(
+index
+) + '' + label + ''
+
+
+def stage_label(stage):
+return stage.op.name + 'Scope: ' + stage.scope
+
+
+def legend_label():
+label = '<'
+for iter_type in ITERVAR_TYPE_STRING_MAP:
+name, color = ITERVAR_TYPE_STRING_MAP[iter_type]
+label += '' \
++ '' + name + ''
+label += '>'
+return label
+
+
+def legend_dot(g):
+with g.subgraph(name='cluster_legend') as subgraph:
+subgraph.attr(label='Legend')
+label = legend_label()
+subgraph.node('legend', label, shape='none', margin='0')
+
+
+def dump_graph(dot_string,
+ showsvg=True,
+ dotfilepath='',
+ outputdotstring=False):
+"""Output dot_string in various formats."""
+if dotfilepath:
+try:
+dot_file = open(dotfilepath, "w+")
+dot_file.write(dot_string)
+dot_file.close()
+except IOError:
+print('Cannot open file: ' + dotfilepath)
+if showsvg:
+src = Source(dot_string)
+
[GitHub] [incubator-tvm] yongfeng-nv commented on a change in pull request #4651: Tensor Expression Debug Display (TEDD)
yongfeng-nv commented on a change in pull request #4651: Tensor Expression
Debug Display (TEDD)
URL: https://github.com/apache/incubator-tvm/pull/4651#discussion_r364318828
##
File path: python/tvm/contrib/tedd.py
##
@@ -0,0 +1,506 @@
+# 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.
+"""Tensor Expression Debug Display (TEDD), visualizing Tensor Expression"""
+import html
+from graphviz import Digraph
+from graphviz import Source
+from IPython.display import display
+from IPython.display import SVG
+import tvm
+
+TVMDD_TABLE_BODY_WIDTH = 30
+# Must match enum IterVarType defined in include/tvm/expr.h
+ITERVAR_TYPE_STRING_MAP = {
+0: ('kDataPar', '#FF'),
+1: ('kThreadIndex', '#2980B9'),
+2: ('kCommReduce', '#FAD7A0'),
+3: ('kOrdered', '#D35400'),
+4: ('kOpaque', '#ABB2B9'),
+5: ('kUnrolled', '#D2B4DE'),
+6: ('kVectorized', '#AED6F1'),
+7: ('kParallelized', '#F5B7B1'),
+8: ('kTensorized', '#A9DFBF'),
+}
+
+
+def get_or_create_dot_id(obj, prefix="", assert_on_missing=False):
+"""If obj's ID has been registered, return it.
+ If not, either assert or create a unique and legal ID, register and
+ return it, according to assert_on_missing.
+ ID must be a unique and legal Dotty ID.
+
+Parameters
+--
+obj : objet
+Serve as the key to the ID.
+
+prefix : string
+Prefix to attach to the ID. Usually use obj's non-unique
+name as prefix.
+
+assert_on_missing : bool
+Asserts or not if object doesn't have a registered ID.
+"""
+prefix = prefix.replace('.', '_')
+if not hasattr(get_or_create_dot_id, "obj_id_dict"):
+get_or_create_dot_id.obj_id_dict = {}
+if obj not in get_or_create_dot_id.obj_id_dict:
+if assert_on_missing:
+assert False, 'dot_id ' + str(obj) + ' has not been registered.'
+else:
+get_or_create_dot_id.obj_id_dict[obj] = prefix + hex(id(obj))
+return get_or_create_dot_id.obj_id_dict[obj]
+
+
+def get_port_id(is_input, index):
+return 'I_' + str(index) if is_input else 'O_' + str(index)
+
+
+def get_itervar_type_info(iter_type):
+assert iter_type < len(
+ITERVAR_TYPE_STRING_MAP), 'Unknown IterVar type: ' + str(iter_type)
+return ITERVAR_TYPE_STRING_MAP[iter_type]
+
+
+def get_itervar_label_color(itervar, iv_type):
+type_info = get_itervar_type_info(iv_type)
+return str(itervar.var) + '(' + type_info[0] + ')', type_info[1]
+
+
+def linebrk(s, n):
+""" Break input string s with for every n charactors."""
+result = ''
+j = 0
+for i, c in enumerate(s):
+if j == n and i != len(s) - 1:
+result = result + '\n'
+j = 0
+j = j + 1
+result = result + c
+result = html.escape(str(result), quote=True)
+result = result.replace('\n', '')
+return result
+
+
+def create_graph(name="", rankdir='BT'):
+graph = Digraph(name=name)
+graph.graph_attr['rankdir'] = rankdir
+return graph
+
+
+def itervar_label(itervar, index, index_color, label):
+return '' + str(
+index
+) + '' + label + ''
+
+
+def stage_label(stage):
+return stage.op.name + 'Scope: ' + stage.scope
+
+
+def legend_label():
+label = '<'
+for iter_type in ITERVAR_TYPE_STRING_MAP:
+name, color = ITERVAR_TYPE_STRING_MAP[iter_type]
+label += '' \
++ '' + name + ''
+label += '>'
+return label
+
+
+def legend_dot(g):
+with g.subgraph(name='cluster_legend') as subgraph:
+subgraph.attr(label='Legend')
+label = legend_label()
+subgraph.node('legend', label, shape='none', margin='0')
+
+
+def dump_graph(dot_string,
+ showsvg=True,
+ dotfilepath='',
+ outputdotstring=False):
+"""Output dot_string in various formats."""
+if dotfilepath:
+try:
+dot_file = open(dotfilepath, "w+")
+dot_file.write(dot_string)
+dot_file.close()
+except IOError:
+print('Cannot open file: ' + dotfilepath)
+if showsvg:
+src = Source(dot_string)
+
