You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/01/13 15:26:38 UTC
[GitHub] [incubator-tvm] inadob opened a new pull request #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
inadob opened a new pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695
- Add support for: greater_equal, less, less_equal, equal, not_equal
- Add tests for the elemwise relational ops
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] wyc-ruiker commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
wyc-ruiker commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r365897665
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -616,6 +621,36 @@ def convert_greater(self, op):
'TFlite quantized greater operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
+ def convert_greater_equal(self, op):
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized GREATER_EQUAL operator is not supported yet.')
Review comment:
The previous operators seem to be all lowercase letters here. Maybe you should use `greater_equal` for consistency. The following operators are the same.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene merged pull request #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene merged pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] inadob commented on a change in pull request #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
inadob commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r371203978
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,77 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
+ # Check if the input tensor is quantized, call QNN op
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized SQUARED_DIFFERENCE operator is not supported yet.')
+ difference = self._convert_elemwise(_op.subtract, op)
+ # _convert_elemwise has guaranteed only have one output tensor
+ exp_type = self.get_tensor_type_str(self.get_output_tensors(op)[0].tensor.Type())
+ out = _op.power(difference, relay.const(2, exp_type))
+ return out
+
def convert_maximum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized maximum operator is not supported yet.')
+ 'TFlite quantized MAXIMUM operator is not supported yet.')
return self._convert_elemwise(_op.maximum, op)
def convert_minimum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized minimum operator is not supported yet.')
+ 'TFlite quantized MINIMUM operator is not supported yet.')
return self._convert_elemwise(_op.minimum, op)
def convert_greater(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized greater operator is not supported yet.')
+ 'TFlite quantized GREATER operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
- def convert_squared_difference(self, op):
- # Check if the input tensor is quantized, call QNN op
+ def convert_greater_equal(self, op):
Review comment:
so do you want me to add such a doc string to every elemwise function or to remove it from 'add', 'sub', 'mul' and 'div'
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r368906216
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,77 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
+ # Check if the input tensor is quantized, call QNN op
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized SQUARED_DIFFERENCE operator is not supported yet.')
+ difference = self._convert_elemwise(_op.subtract, op)
+ # _convert_elemwise has guaranteed only have one output tensor
+ exp_type = self.get_tensor_type_str(self.get_output_tensors(op)[0].tensor.Type())
+ out = _op.power(difference, relay.const(2, exp_type))
+ return out
+
def convert_maximum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized maximum operator is not supported yet.')
+ 'TFlite quantized MAXIMUM operator is not supported yet.')
return self._convert_elemwise(_op.maximum, op)
def convert_minimum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized minimum operator is not supported yet.')
+ 'TFlite quantized MINIMUM operator is not supported yet.')
return self._convert_elemwise(_op.minimum, op)
def convert_greater(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized greater operator is not supported yet.')
+ 'TFlite quantized GREATER operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
- def convert_squared_difference(self, op):
- # Check if the input tensor is quantized, call QNN op
+ def convert_greater_equal(self, op):
Review comment:
Last captious comment.:-) We omit the doc string of function. For example, """ Convert TFLite greater equal op """ like other functions.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r368262762
##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -722,6 +722,42 @@ def _test_minimum(data):
def _test_greater(data):
""" One iteration of greater """
return _test_elemwise(math_ops.greater, data)
+#######################################################################
+# Greater_equal
+# -------------
+
+def _test_greater_equal(data):
+ """ One iteration of greater_equal """
+ return _test_elemwise(math_ops.greater_equal, data)
+#######################################################################
+# Less
+# ----
+
+def _test_less(data):
+ """ One iteration of less """
+ return _test_elemwise(math_ops.less, data)
+#######################################################################
+# Less_equal
+# ----------
+
+def _test_less_equal(data):
+ """ One iteration of less_equal """
+ return _test_elemwise(math_ops.less_equal, data)
+#######################################################################
+# Equal
+# -----
+
+def _test_equal(data):
+ """ One iteration of equal """
+ return _test_elemwise(math_ops.equal, data)
+#######################################################################
+# Not_equal
+# ---------
+
+def _test_not_equal(data):
+ """ One iteration of not_equal"""
+ return _test_elemwise(math_ops.not_equal, data)
+#######################################################################
Review comment:
Yes. one redundant line . Pls remove it.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] wyc-ruiker commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
wyc-ruiker commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r365896079
##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -722,6 +722,42 @@ def _test_minimum(data):
def _test_greater(data):
""" One iteration of greater """
return _test_elemwise(math_ops.greater, data)
+#######################################################################
+# Greater_equal
+# -------------
+
+def _test_greater_equal(data):
+ """ One iteration of greater_equal """
+ return _test_elemwise(math_ops.greater_equal, data)
+#######################################################################
+# Less
+# ----
+
+def _test_less(data):
+ """ One iteration of less """
+ return _test_elemwise(math_ops.less, data)
+#######################################################################
+# Less_equal
+# ----------
+
+def _test_less_equal(data):
+ """ One iteration of less_equal """
+ return _test_elemwise(math_ops.less_equal, data)
+#######################################################################
+# Equal
+# -----
+
+def _test_equal(data):
+ """ One iteration of equal """
+ return _test_elemwise(math_ops.equal, data)
+#######################################################################
+# Not_equal
+# ---------
+
+def _test_not_equal(data):
+ """ One iteration of not_equal"""
+ return _test_elemwise(math_ops.not_equal, data)
+#######################################################################
Review comment:
I think there should be no `#########` here?
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] inadob commented on a change in pull request #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
inadob commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r365927427
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -616,6 +621,36 @@ def convert_greater(self, op):
'TFlite quantized greater operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
+ def convert_greater_equal(self, op):
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized GREATER_EQUAL operator is not supported yet.')
Review comment:
From my perspective, when the operator is in lowercase it somehow mixes with the rest of the sentence so writing in capitals makes it a bit more clear... imagine this is not the only error you get in the console. Anyway, I am open to suggestions :)
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r368262724
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -616,6 +621,36 @@ def convert_greater(self, op):
'TFlite quantized greater operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
+ def convert_greater_equal(self, op):
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized GREATER_EQUAL operator is not supported yet.')
Review comment:
Seems that we have two styles of it. Some code use `lowercase` like `convert_greater`, some code use `uppercase` like `convert_neg`. I think we should unify them to `uppercase`. Two reasons: 1. it corresponds to our `convert_map` / tflite operator string represenation. 2. it could make us catch the operator more quickly in one sentence like @inadob said. So @inadob could you help to update other code to `uppercase` too? Thanks.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] inadob commented on issue #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
inadob commented on issue #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#issuecomment-573719645
@anijain2305 @FrozenGene, can you please review this PR
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r372450103
##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -843,6 +843,13 @@ def _test_pow(data):
""" One iteration of power """
return _test_elemwise(math_ops.pow, data)
#######################################################################
+# Squared_difference
+# ------------------
+
+def _test_squared_difference(data):
Review comment:
Same problem as previous comment. Please correct it.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on issue #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on issue #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#issuecomment-580271032
Thanks @inadob @wyc-ruiker This is merged now.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] wyc-ruiker commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
wyc-ruiker commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r368908200
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,77 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
+ # Check if the input tensor is quantized, call QNN op
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized SQUARED_DIFFERENCE operator is not supported yet.')
+ difference = self._convert_elemwise(_op.subtract, op)
+ # _convert_elemwise has guaranteed only have one output tensor
+ exp_type = self.get_tensor_type_str(self.get_output_tensors(op)[0].tensor.Type())
+ out = _op.power(difference, relay.const(2, exp_type))
+ return out
+
def convert_maximum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized maximum operator is not supported yet.')
+ 'TFlite quantized MAXIMUM operator is not supported yet.')
return self._convert_elemwise(_op.maximum, op)
def convert_minimum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized minimum operator is not supported yet.')
+ 'TFlite quantized MINIMUM operator is not supported yet.')
return self._convert_elemwise(_op.minimum, op)
def convert_greater(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized greater operator is not supported yet.')
+ 'TFlite quantized GREATER operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
- def convert_squared_difference(self, op):
Review comment:
Please rebase from master.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r372449323
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,87 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
+ """Convert TFLite POW"""
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
Review comment:
This part shouldn’t appear in your pr if you rebase master correctly. Seems that you don’t handle it correctly and move this implementation manually. Please rebase your pr to master correctly referring this: https://docs.tvm.ai/contribute/git_howto.html
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] FrozenGene commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r371276409
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,77 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
+ # Check if the input tensor is quantized, call QNN op
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized SQUARED_DIFFERENCE operator is not supported yet.')
+ difference = self._convert_elemwise(_op.subtract, op)
+ # _convert_elemwise has guaranteed only have one output tensor
+ exp_type = self.get_tensor_type_str(self.get_output_tensors(op)[0].tensor.Type())
+ out = _op.power(difference, relay.const(2, exp_type))
+ return out
+
def convert_maximum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized maximum operator is not supported yet.')
+ 'TFlite quantized MAXIMUM operator is not supported yet.')
return self._convert_elemwise(_op.maximum, op)
def convert_minimum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized minimum operator is not supported yet.')
+ 'TFlite quantized MINIMUM operator is not supported yet.')
return self._convert_elemwise(_op.minimum, op)
def convert_greater(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized greater operator is not supported yet.')
+ 'TFlite quantized GREATER operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
- def convert_squared_difference(self, op):
- # Check if the input tensor is quantized, call QNN op
+ def convert_greater_equal(self, op):
Review comment:
add such a doc string to every elemwise function.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] wyc-ruiker commented on a change in pull request
#4695: [Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
wyc-ruiker commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r368908200
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -705,47 +710,77 @@ def convert_div(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized div operator is not supported yet.')
+ 'TFlite quantized DIV operator is not supported yet.')
return self._convert_elemwise(_op.divide, op)
def convert_pow(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized pow operator is not supported yet.')
+ 'TFlite quantized POW operator is not supported yet.')
return self._convert_elemwise(_op.power, op)
+ def convert_squared_difference(self, op):
+ # Check if the input tensor is quantized, call QNN op
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized SQUARED_DIFFERENCE operator is not supported yet.')
+ difference = self._convert_elemwise(_op.subtract, op)
+ # _convert_elemwise has guaranteed only have one output tensor
+ exp_type = self.get_tensor_type_str(self.get_output_tensors(op)[0].tensor.Type())
+ out = _op.power(difference, relay.const(2, exp_type))
+ return out
+
def convert_maximum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized maximum operator is not supported yet.')
+ 'TFlite quantized MAXIMUM operator is not supported yet.')
return self._convert_elemwise(_op.maximum, op)
def convert_minimum(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized minimum operator is not supported yet.')
+ 'TFlite quantized MINIMUM operator is not supported yet.')
return self._convert_elemwise(_op.minimum, op)
def convert_greater(self, op):
# Check if the input tensor is quantized, call QNN op
if self.is_quantized(op):
raise tvm.error.OpNotImplemented(
- 'TFlite quantized greater operator is not supported yet.')
+ 'TFlite quantized GREATER operator is not supported yet.')
return self._convert_elemwise(_op.greater, op)
- def convert_squared_difference(self, op):
Review comment:
Please rebase from master.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services
[GitHub] [incubator-tvm] inadob commented on a change in pull request #4695:
[Relay][Frontend][TFlite] Add parser support for relational ops
Posted by GitBox <gi...@apache.org>.
inadob commented on a change in pull request #4695: [Relay][Frontend][TFlite] Add parser support for relational ops
URL: https://github.com/apache/incubator-tvm/pull/4695#discussion_r372861913
##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -843,6 +843,13 @@ def _test_pow(data):
""" One iteration of power """
return _test_elemwise(math_ops.pow, data)
#######################################################################
+# Squared_difference
+# ------------------
+
+def _test_squared_difference(data):
Review comment:
Done now
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
With regards,
Apache Git Services