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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/10/17 00:49:24 UTC
[GitHub] [tvm] electriclilies commented on a change in pull request #9282: [CORE][Relay] Swap and remove compile_engine with te_compiler followup of #8775
electriclilies commented on a change in pull request #9282:
URL: https://github.com/apache/tvm/pull/9282#discussion_r730058969
##########
File path: python/tvm/relay/backend/te_compiler.py
##########
@@ -275,6 +256,46 @@ def select_implementation(op, attrs, inputs, out_type, target, use_autotvm=True)
return best_plevel_impl, outputs[best_plevel_impl]
+@tvm._ffi.register_object("relay.TECompiler")
+class TECompiler(Object):
+ """TECompiler to get lowered code."""
+
+ def __init__(self):
+ raise RuntimeError("Cannot construct a TECompiler")
+
+ def lower(self, source_func, target=None, mod_name="default"):
+ """Lower a source_func to a CachedFunc.
+
+ Parameters
+ ----------
+ source_func : Union[tvm.relay.Function, CCacheKey]
+ The source relay function.
+
+ target : tvm.Target
+ The target platform.
+
+ Returns
+ -------
+ cached_func: CachedFunc
+ The result of lowering.
+ """
+ # pylint: disable=broad-except, import-outside-toplevel
+ try:
+ mod_name = mangle_module_name(mod_name)
+ key = _get_cache_key(source_func, target)
+ print(key)
Review comment:
A stray print!
##########
File path: python/tvm/relay/backend/te_compiler.py
##########
@@ -79,24 +78,6 @@ def _get_cache_key(source_func, target):
return source_func
-def get_shape(shape):
- """Convert the shape to correct dtype and vars."""
- ret = []
- for dim in shape:
- if isinstance(dim, tvm.tir.IntImm):
- if libinfo()["INDEX_DEFAULT_I64"] == "ON":
- ret.append(dim)
- else:
- val = int(dim)
- assert val <= np.iinfo(np.int32).max
- ret.append(tvm.tir.IntImm("int32", val))
- elif isinstance(dim, tvm.tir.Any):
- ret.append(te.var("any_dim", "int32"))
- else:
- ret.append(dim)
- return ret
-
-
Review comment:
What is this replaced with?
##########
File path: tests/python/contrib/test_vitis_ai/infrastructure.py
##########
@@ -18,24 +18,23 @@
"""Expose Vitis-AI test functions to the Python frontend"""
+from tvm.contrib import utils
+from tvm.contrib import graph_executor
+from tvm.contrib.target import vitis_ai
+from tvm.relay.build_module import bind_params_by_name
+from tvm.relay.op.contrib.vitis_ai import partition_for_vitis_ai
+from tvm.relay import transform
+from tvm import runtime
+from tvm import relay
+import tvm
+import pyxir.contrib.target.DPUCZDX8G
+import pyxir.contrib.target.DPUCADX8G
import sys
Review comment:
Did you mean to reorder this? looks like now you are importing pyxir before the pytest.importorskip("pyxir") line.
##########
File path: python/tvm/relay/backend/te_compiler.py
##########
@@ -275,6 +256,46 @@ def select_implementation(op, attrs, inputs, out_type, target, use_autotvm=True)
return best_plevel_impl, outputs[best_plevel_impl]
+@tvm._ffi.register_object("relay.TECompiler")
+class TECompiler(Object):
+ """TECompiler to get lowered code."""
+
+ def __init__(self):
+ raise RuntimeError("Cannot construct a TECompiler")
+
+ def lower(self, source_func, target=None, mod_name="default"):
+ """Lower a source_func to a CachedFunc.
+
+ Parameters
+ ----------
+ source_func : Union[tvm.relay.Function, CCacheKey]
+ The source relay function.
+
+ target : tvm.Target
+ The target platform.
+
+ Returns
+ -------
+ cached_func: CachedFunc
+ The result of lowering.
+ """
+ # pylint: disable=broad-except, import-outside-toplevel
+ try:
+ mod_name = mangle_module_name(mod_name)
Review comment:
Why do name mangling here instead of in TECompilerLower?
##########
File path: python/tvm/relay/backend/te_compiler.py
##########
@@ -79,24 +78,6 @@ def _get_cache_key(source_func, target):
return source_func
-def get_shape(shape):
- """Convert the shape to correct dtype and vars."""
- ret = []
- for dim in shape:
- if isinstance(dim, tvm.tir.IntImm):
- if libinfo()["INDEX_DEFAULT_I64"] == "ON":
- ret.append(dim)
- else:
- val = int(dim)
- assert val <= np.iinfo(np.int32).max
- ret.append(tvm.tir.IntImm("int32", val))
- elif isinstance(dim, tvm.tir.Any):
- ret.append(te.var("any_dim", "int32"))
- else:
- ret.append(dim)
- return ret
-
-
Review comment:
Oops, now I see this was just moved. Nevermind
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