anijain2305 commented on a change in pull request #6955:
URL: https://github.com/apache/tvm/pull/6955#discussion_r532748263
##########
File path: python/tvm/relay/op/contrib/tensorrt.py
##########
@@ -198,6 +198,18 @@ def _func_wrapper(expr):
if any([x.checked_type.dtype != "float32" for x in args]):
logger.info("Only float32 inputs are supported for TensorRT.")
return False
+ if op_name == "multiply":
+ shapes = [
+ [
+ int(x) if not isinstance(x, tvm.tir.expr.Any) else -1
+ for x in arg.checked_type.shape
+ ]
+ for arg in args
+ ]
+ if all(
Review comment:
Please add a comment why this shape is important
##########
File path: tests/scripts/task_ci_python_setup.sh
##########
@@ -31,3 +31,4 @@ set -o pipefail
echo "Addtiional setup in" ${CI_IMAGE_NAME}
python3 -m pip install --user tlcpack-sphinx-addon==0.1.2 synr==0.2.1
+python3 -m pip install --user torch==1.6.0+cpu torchvision==0.7.0+cpu -f
https://download.pytorch.org/whl/torch_stable.html
Review comment:
Not sure if we can do this. @zhiics
##########
File path: python/tvm/relay/op/contrib/tensorrt.py
##########
@@ -795,6 +839,38 @@ def conv3d_transpose_annotate_fn(expr): # pylint:
disable=unused-variable
return True
+class IsComputeIntensiveGraph(ExprVisitor):
+ """
+ Visits the Graph recursively and checks if it contains compute heavy ops
like convolutions and
+ its transpose, dense and batch mat-mul.
+ """
+
+ def __init__(self):
+ ExprVisitor.__init__(self)
+ self.is_compute_intensive = False
+
+ def visit_call(self, call):
+ heavy_ops = set(
Review comment:
s/heavy_ops/compute_intensive_ops/
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