szha closed pull request #10083: [TENSOR] Fix DLTensor conversion for int64
URL: https://github.com/apache/incubator-mxnet/pull/10083
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diff --git a/include/mxnet/tensor_blob.h b/include/mxnet/tensor_blob.h
index 59c1eacb2c5..6f604a5bb8d 100755
--- a/include/mxnet/tensor_blob.h
+++ b/include/mxnet/tensor_blob.h
@@ -322,16 +322,19 @@ class TBlob {
private:
static DLDataType DTypeTransform(int type_flag) {
- static std::unordered_map<int, DLDataType>
- MSHADOW_DTYPE_TO_DLPACK_DTYPE = {
- {0, {2, 32, 1}}, // Float32
- {1, {2, 64, 1}}, // Float64
- {2, {2, 16, 1}}, // Float16
- {3, {1, 8, 1}}, // UInt8
- {4, {0, 32, 1}}, // Int32
- {5, {0, 8, 1}} // Int8
- };
- return MSHADOW_DTYPE_TO_DLPACK_DTYPE[type_flag];
+ switch (type_flag) {
+ case mshadow::kFloat32: return DLDataType{kDLFloat, 32, 1};
+ case mshadow::kFloat64: return DLDataType{kDLFloat, 64, 1};
+ case mshadow::kFloat16: return DLDataType{kDLFloat, 16, 1};
+ case mshadow::kUint8: return DLDataType{kDLUInt, 8, 1};
+ case mshadow::kInt32: return DLDataType{kDLInt, 32, 1};
+ case mshadow::kInt8: return DLDataType{kDLInt, 8, 1};
+ case mshadow::kInt64: return DLDataType{kDLInt, 64, 1};
+ default: {
+ LOG(FATAL) << "Unknown type_flag=" << type_flag;
+ return DLDataType();
+ }
+ }
}
inline void SetDLTensor(int dev_mask, int dev_id) {
diff --git a/tests/python/gpu/test_tvm_bridge.py
b/tests/python/gpu/test_tvm_bridge.py
index 292b9d91e5f..69a713d6a28 100644
--- a/tests/python/gpu/test_tvm_bridge.py
+++ b/tests/python/gpu/test_tvm_bridge.py
@@ -30,13 +30,13 @@ def test_tvm_bridge():
logging.warn("TVM bridge test skipped because TVM is missing...")
return
- def check(target):
+ def check(target, dtype):
shape = (20,)
scale = tvm.var("scale", dtype="float32")
- x = tvm.placeholder(shape)
- y = tvm.placeholder(shape)
+ x = tvm.placeholder(shape, dtype=dtype)
+ y = tvm.placeholder(shape, dtype=dtype)
z = tvm.compute(shape, lambda i: x[i] + y[i])
- zz = tvm.compute(shape, lambda *i: z(*i) * scale)
+ zz = tvm.compute(shape, lambda *i: z(*i) * scale.astype(dtype))
ctx = mx.gpu(0) if target == "cuda" else mx.cpu(0)
target = tvm.target.create(target)
@@ -47,17 +47,18 @@ def check(target):
# get a mxnet version
mxf = tvm.contrib.mxnet.to_mxnet_func(f, const_loc=[0, 1])
- xx = mx.nd.uniform(shape=shape, ctx=ctx)
- yy = mx.nd.uniform(shape=shape, ctx=ctx)
- zz = mx.nd.empty(shape=shape, ctx=ctx)
+ xx = mx.nd.uniform(shape=shape, ctx=ctx).astype(dtype)
+ yy = mx.nd.uniform(shape=shape, ctx=ctx).astype(dtype)
+ zz = mx.nd.empty(shape=shape, ctx=ctx).astype(dtype)
# invoke myf: this runs in mxnet engine
mxf(xx, yy, zz, 10.0)
np.testing.assert_allclose(
zz.asnumpy(), (xx.asnumpy() + yy.asnumpy()) * 10)
- check("llvm")
- check("cuda")
-
+ for tgt in ["llvm", "cuda"]:
+ for dtype in ["int8", "uint8", "int64",
+ "float32", "float64"]:
+ check(tgt, dtype)
if __name__ == "__main__":
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