[Pylint] Pylint integration_tests folder (apache#11672)

* add folder to pylint

* add init py

* lint test_arm_mrpofile_dsp.py

* one more change to tests/python/integratoin/test_arm_mprofile_dsp.py

* add test_dot

* test_ewise_fpga.py

* test_ewise.py

* test gemm

* test_lower.py

* test_meta_schedule_auto_tensorize.py

* test_reduce.py pt1

* test_reduce.py pt2

* test_scan.py

* test_tuning.py

* test_winograd_nnpack.py

* final test pass

* comments

* clean up test_lower more

tests/lint/pylint.sh

@@ -23,3 +23,4 @@ python3 -m pylint tests/python/unittest/test_tvmscript_type.py --rcfile="$(dirna
 python3 -m pylint tests/python/contrib/test_cmsisnn --rcfile="$(dirname "$0")"/pylintrc
 python3 -m pylint tests/python/relay/aot/*.py --rcfile="$(dirname "$0")"/pylintrc
 python3 -m pylint tests/python/ci --rcfile="$(dirname "$0")"/pylintrc
+python3 -m pylint tests/python/integration/ --rcfile="$(dirname "$0")"/pylintrc

tests/python/integration/__init__.py

@@ -0,0 +1,17 @@
+# 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.
+"""Infrastructure and tests for e2e integration tests."""

tests/python/integration/test_arm_mprofile_dsp.py

@@ -14,7 +14,7 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
-import sys
+"""Test arm mprofile dsp."""
 import numpy as np
 import pytest
 import tvm
@@ -173,16 +173,16 @@ def test_conv1d(data_shape_nwc, kernel_size, num_filter, strides, padding, dtype
 
 @tvm.testing.requires_corstone300
 @pytest.mark.parametrize(
-    "M, K, N",
+    "dim_m, dim_k, dim_n",
     [
         (1, 32, 64),
         (3, 12, 10),
     ],
 )
-def test_dense(M, K, N):
+def test_dense(dim_m, dim_k, dim_n):
     """Test a subgraph with a single dense operator."""
-    ishape = (M, K)
-    wshape = (N, K)
+    ishape = (dim_m, dim_k)
+    wshape = (dim_n, dim_k)
 
     input0 = relay.var("input", relay.TensorType(ishape, "int8"))
     dense_f = relay.op.nn.batch_flatten(input0)

tests/python/integration/test_dot.py

@@ -14,31 +14,46 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+"""Test scheduling and running a dot product."""
+import numpy as np
+
 import tvm
 import tvm.testing
 from tvm import te
-import numpy as np
 
 
 @tvm.testing.requires_llvm
 def test_dot():
-    nn = 12
-    n = tvm.runtime.convert(nn)
-    A = te.placeholder((n,), name="A")
-    B = te.placeholder((n,), name="B")
-    k = te.reduce_axis((0, n), "k")
-    C = te.compute((), lambda: te.sum(A[k] * B[k], axis=k), name="C")
-    s = te.create_schedule(C.op)
+    """Test dot product."""
+    arr_length = 12
+    arr_length_tvm = tvm.runtime.convert(arr_length)
+    placeholder_a = te.placeholder((arr_length_tvm,), name="A")
+    placeholder_b = te.placeholder((arr_length_tvm,), name="B")
+    reduce_axis_k = te.reduce_axis((0, arr_length_tvm), "k")
+    result_c = te.compute(
+        (),
+        lambda: te.sum(
+            placeholder_a[reduce_axis_k] * placeholder_b[reduce_axis_k], axis=reduce_axis_k
+        ),
+        name="C",
+    )
+    schedule = te.create_schedule(result_c.op)
 
     def verify(target):
-        f = tvm.driver.build(s, [A, B, C], target)
+        f = tvm.driver.build(schedule, [placeholder_a, placeholder_b, result_c], target)
         # verify
         dev = tvm.cpu(0)
-        a = tvm.nd.array(np.random.uniform(size=(nn,)).astype(A.dtype), dev)
-        b = tvm.nd.array(np.random.uniform(size=(nn,)).astype(B.dtype), dev)
-        c = tvm.nd.array(np.zeros((), dtype=C.dtype), dev)
-        f(a, b, c)
-        tvm.testing.assert_allclose(c.numpy(), np.dot(a.numpy(), b.numpy()), rtol=1e-4)
+        buff_a = tvm.nd.array(
+            np.random.uniform(size=(arr_length,)).astype(placeholder_a.dtype), dev
+        )
+        buff_b = tvm.nd.array(
+            np.random.uniform(size=(arr_length,)).astype(placeholder_b.dtype), dev
+        )
+        buff_c = tvm.nd.array(np.zeros((), dtype=result_c.dtype), dev)
+        f(buff_a, buff_b, buff_c)
+        tvm.testing.assert_allclose(
+            buff_c.numpy(), np.dot(buff_a.numpy(), buff_b.numpy()), rtol=1e-4
+        )
 
     verify("llvm")