rahul003 closed pull request #10538: [MXNET-318] Allow dot for fp16 on GPU
URL: https://github.com/apache/incubator-mxnet/pull/10538
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diff --git a/src/operator/tensor/dot-inl.h b/src/operator/tensor/dot-inl.h
index c5f278e78a4..a6833c288cc 100644
--- a/src/operator/tensor/dot-inl.h
+++ b/src/operator/tensor/dot-inl.h
@@ -69,9 +69,10 @@ void DotForward_(const nnvm::NodeAttrs& attrs,
<< "Binary function only support input/output with the same type";
CHECK_EQ(outputs[0].type_flag_, inputs[1].type_flag_)
<< "Binary function only support input/output with the same type";
- CHECK(outputs[0].type_flag_ == kFloat32 || outputs[0].type_flag_ == kFloat64)
- << "dot only supports float32 and float64";
- MSHADOW_SGL_DBL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
+ CHECK(outputs[0].type_flag_ == kFloat32 || outputs[0].type_flag_ == kFloat64
||
+ ctx.run_ctx.ctx.dev_mask() == mshadow::gpu::kDevMask)
+ << "dot only supports float32/float64 for CPU, and
float16/float32/float64 for GPU";
+ MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
if (inputs[0].ndim() == 1 && inputs[1].ndim() == 1) {
CHECK_NE(req[0], kAddTo) << "AddTo not yet supported";
Tensor<xpu, 1, DType> out = outputs[0].get<xpu, 1, DType>(s);
@@ -129,7 +130,7 @@ void DotBackward_(const nnvm::NodeAttrs& attrs,
Stream<xpu> *s = ctx.get_stream<xpu>();
CHECK_NE(req[0], kWriteInplace);
CHECK_NE(req[1], kWriteInplace);
- MSHADOW_SGL_DBL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
+ MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
if (inputs[1].ndim() == 1 && inputs[2].ndim() == 1) {
Tensor<xpu, 1, DType> mout_grad = inputs[0].get<xpu, 1, DType>(s);
Tensor<xpu, 1, DType> mlhs_data = inputs[1].get<xpu, 1, DType>(s);
diff --git a/tests/python/unittest/test_operator.py
b/tests/python/unittest/test_operator.py
index 5d382220a7a..78fd84145ec 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -2070,7 +2070,7 @@ def test_stn():
@with_seed(1234)
def test_dot():
ctx=default_context()
- dtypes = ['float32', 'float64']
+ dtypes = ['float16', 'float32', 'float64']
# Test normal dot.
for data_type in dtypes:
@@ -2094,10 +2094,16 @@ def test_dot():
c = mx.sym.dot(a, b)
exe = c.simple_bind(ctx=ctx, a=a_npy.shape, b=b_npy.shape)
outputs = exe.forward(is_train=True, a=a_npy, b=b_npy)
- assert_almost_equal(outputs[0].asnumpy(), c_npy, rtol=1e-3)
- exe.backward(out_grads=[mx.nd.array(ograd_npy, mx.cpu())])
- assert_almost_equal(exe.grad_dict['a'].asnumpy(),
agrad_npy, rtol=1e-3)
- assert_almost_equal(exe.grad_dict['b'].asnumpy(),
bgrad_npy, rtol=1e-3)
+ assert_almost_equal(outputs[0].asnumpy(), c_npy,
+ rtol=1e-2 if data_type == 'float16'
else 1e-3,
+ atol=1e-2 if data_type == 'float16'
else 1e-3)
+ exe.backward(out_grads=[mx.nd.array(ograd_npy,
mx.cpu()).astype(data_type)])
+ assert_almost_equal(exe.grad_dict['a'].asnumpy(),
agrad_npy,
+ rtol=1e-2 if data_type == 'float16'
else 1e-3,
+ atol=1e-2 if data_type == 'float16'
else 1e-3)
+ assert_almost_equal(exe.grad_dict['b'].asnumpy(),
bgrad_npy,
+ rtol=1e-2 if data_type == 'float16'
else 1e-3,
+ atol=1e-2 if data_type == 'float16'
else 1e-3)
# Test dot with transpose flag using gradient checker.
def dot_sym(data_type):
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