Change const to used dtype if it is passed in

python/tvm/relay/expr.py

@@ -488,7 +488,7 @@ def const(value, dtype=None):
         The constant value.
 
     dtype: str, optional
-        The data type of the value.
+        The data type of the resulting constant.
 
     Note
     ----
@@ -504,13 +504,13 @@ def const(value, dtype=None):
 
     if not dtype:
         # when dtype is None: int maps to "int32", float maps to "float32"
-        map_dtype = {_np.dtype("int64"): _np.int32, _np.dtype("float64"): _np.float32}.get(
+        dtype = {_np.dtype("int64"): _np.int32, _np.dtype("float64"): _np.float32}.get(
             value.dtype, None
         )
-        if map_dtype:
-            value = value.astype(map_dtype)
 
     if isinstance(value, (_np.ndarray, _np.generic)):
+        if dtype is not None:
+            value = value.astype(dtype)
         value = _nd.array(value)
 
     if not isinstance(value, _nd.NDArray):

tests/python/relay/test_const.py

@@ -0,0 +1,44 @@
+# 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 tvm
+import numpy as np
+from tvm import relay
+from tvm.relay.frontend.common import infer_type
+from tvm.relay import op as _op
+
+
+def test_const_dtype():
+    strides = (1, 1)
+    np_array = np.array(strides).astype("int32")
+    strides = _op.const(np_array, dtype="int64")
+
+    # strides needs to be autoconverted to int64 on Windows
+    assert infer_type(strides).checked_type.dtype == np.dtype(np.int64)
+
+    a = tvm.nd.array(np.random.randint(0, high=255, size=(2, 3), dtype="uint8"))
+    a = _op.const(a, dtype="uint8")
+    aa = a.data.asnumpy()
+    assert aa.dtype == np.dtype(np.uint8)
+
+    b = _op.const(1, dtype="int8")
+    bb = b.data.asnumpy()
+    assert bb.dtype == np.dtype(np.int8)
+
+    kshape = (3, 10, 3, 3)
+    w = relay.const(np.zeros(kshape, dtype="float32"))
+    assert w.data.asnumpy().dtype == np.dtype(np.float32)