[GitHub] [tvm] areusch commented on a change in pull request #8469: [TIR][USMP] Add a parallel to serial for loop converter pass

[GitBox <gi...@apache.org>]

areusch commented on a change in pull request #8469:
URL: https://github.com/apache/tvm/pull/8469#discussion_r707535161



##########
File path: tests/python/unittest/test_tir_transform_convert_for_loops_serial.py
##########
@@ -0,0 +1,62 @@
+# 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 pytest
+
+import tvm
+from tvm import tir, script
+from tvm.script import ty
+from tvm.tir import stmt_functor
+
+# fmt: off
+@tvm.script.tir
+def fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_2(placeholder_30: ty.handle, placeholder_31: ty.handle, placeholder_32: ty.handle, T_cast_8: ty.handle) -> None:
+    # function attr dict
+    tir.func_attr({"global_symbol": "fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_2", "tir.noalias": True})
+    placeholder_33 = tir.match_buffer(placeholder_30, [1, 28, 28, 192], dtype="int16", elem_offset=0, align=128, offset_factor=1)
+    placeholder_34 = tir.match_buffer(placeholder_31, [1, 1, 192, 16], dtype="int16", elem_offset=0, align=128, offset_factor=1)
+    placeholder_35 = tir.match_buffer(placeholder_32, [1, 1, 1, 16], dtype="int32", elem_offset=0, align=128, offset_factor=1)
+    T_cast_9 = tir.match_buffer(T_cast_8, [1, 28, 28, 16], dtype="int16", elem_offset=0, align=128, offset_factor=1)
+    # body
+    PaddedInput_3 = tir.allocate([1, 28, 28, 192], "int16", "global")
+    for i0_i1_fused_3 in tir.parallel(0, 28):
+        for i2_3, i3_3 in tir.grid(28, 192):
+            tir.store(PaddedInput_3, (((i0_i1_fused_3*5376) + (i2_3*192)) + i3_3), tir.load("int16", placeholder_33.data, (((i0_i1_fused_3*5376) + (i2_3*192)) + i3_3)), True)
+    for ax0_ax1_fused_ax2_fused_3 in tir.parallel(0, 784):
+        for ax3_2 in tir.serial(0, 16):
+            Conv2dOutput_3 = tir.allocate([1, 1, 1, 1], "int32", "global")
+            tir.store(Conv2dOutput_3, 0, 0, True)
+            for rc_3 in tir.serial(0, 192):
+                tir.store(Conv2dOutput_3, 0, (tir.load("int32", Conv2dOutput_3, 0) + (tir.cast(tir.load("int16", PaddedInput_3, ((ax0_ax1_fused_ax2_fused_3*192) + rc_3)), "int32")*tir.cast(tir.load("int16", placeholder_34.data, ((rc_3*16) + ax3_2)), "int32"))), True)
+            tir.store(T_cast_9.data, ((ax0_ax1_fused_ax2_fused_3*16) + ax3_2), tir.cast(tir.cast(tir.max(tir.min(tir.q_multiply_shift((tir.load("int32", Conv2dOutput_3, 0) + tir.load("int32", placeholder_35.data, ax3_2)), 1764006585, 31, -7, dtype="int32"), 255), 0), "uint8"), "int16"), True)
+# fmt: on
+
+
+def test_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_2():
+    primfunc = fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_2
+    mod = tvm.IRModule.from_expr(primfunc)

Review comment:
       want to assert that you find at least one kParallel for loop in here?




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