!10006 support int32 dtype of Mul cpu op

From: @wuxuejian
Reviewed-by: @kisnwang,@c_34
Signed-off-by: @c_34

mindspore/ccsrc/backend/kernel_compiler/cpu/arithmetic_cpu_kernel.h

@@ -105,6 +105,9 @@ MS_REG_CPU_KERNEL(
 MS_REG_CPU_KERNEL(
   AssignAdd, KernelAttr().AddInputAttr(kNumberTypeInt64).AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64),
   ArithmeticCPUKernel);
+MS_REG_CPU_KERNEL(
+  Mul, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
+  ArithmeticCPUKernel);
 }  // namespace kernel
 }  // namespace mindspore
 

tests/st/ops/cpu/test_mul_op.py

@@ -84,3 +84,54 @@ def test_mul():
     err = np.ones(shape=exp.shape) * 1.0e-5
     assert np.all(diff < err)
     assert out.shape == exp.shape
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.env_onecard
+def test_mul_int32():
+    x0 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.int32))
+    y0 = Tensor(np.random.uniform(-2, 2, (1, 1, 1, 1)).astype(np.int32))
+    x1 = Tensor(np.random.uniform(-2, 2, (1, 3, 1, 4)).astype(np.int32))
+    y1 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.int32))
+    x2 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.int32))
+    y2 = Tensor(2, mstype.int32)
+    x3 = Tensor(2, mstype.int32)
+    y3 = Tensor(2, mstype.int32)
+    x4 = Tensor(np.random.uniform(-2, 2, (4)).astype(np.int32))
+    y4 = Tensor(np.random.uniform(-2, 2, (4, 4)).astype(np.int32))
+    mul = Net()
+    out = mul(x0, y0).asnumpy()
+    exp = x0.asnumpy() * y0.asnumpy()
+    diff = np.abs(out - exp)
+    err = np.ones(shape=exp.shape) * 1.0e-5
+    assert np.all(diff < err)
+    assert out.shape == exp.shape
+
+    out = mul(x1, y1).asnumpy()
+    exp = x1.asnumpy() * y1.asnumpy()
+    diff = np.abs(out - exp)
+    err = np.ones(shape=exp.shape) * 1.0e-5
+    assert np.all(diff < err)
+    assert out.shape == exp.shape
+
+    out = mul(x2, y2).asnumpy()
+    exp = x2.asnumpy() * y2.asnumpy()
+    diff = np.abs(out - exp)
+    err = np.ones(shape=exp.shape) * 1.0e-5
+    assert np.all(diff < err)
+    assert out.shape == exp.shape
+
+    out = mul(x3, y3).asnumpy()
+    exp = x3.asnumpy() * y3.asnumpy()
+    diff = np.abs(out - exp)
+    err = np.ones(shape=exp.shape) * 1.0e-5
+    assert np.all(diff < err)
+    assert out.shape == exp.shape
+
+    out = mul(x4, y4).asnumpy()
+    exp = x4.asnumpy() * y4.asnumpy()
+    diff = np.abs(out - exp)
+    err = np.ones(shape=exp.shape) * 1.0e-5
+    assert np.all(diff < err)
+    assert out.shape == exp.shape