commit
68bdcb4e62
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@ -185,14 +185,6 @@ bool Tensor::operator==(const Tensor &tensor) const {
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return (MetaTensor::operator==(tensor) && data_ == tensor.data_);
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}
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bool Tensor::ValueEqualPy(const py::object &other) const {
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if (!py::isinstance<Tensor>(other)) {
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MS_LOG(WARNING) << "compare other not a tensor";
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return false;
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}
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return ValueEqual(py::cast<Tensor>(other));
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}
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bool Tensor::ValueEqual(const Tensor &other) const {
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auto equal = [&other, this]() -> bool {
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auto np = py::module::import("numpy");
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@ -542,7 +534,6 @@ REGISTER_PYBIND_DEFINE(Tensor, ([](const py::module *m) {
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)mydelimiter")
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.def("__str__", &Tensor::ToString)
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.def("__repr__", &Tensor::ToStringRepr)
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.def("__eq__", &Tensor::ValueEqualPy)
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.def(py::pickle(
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[](const Tensor &t) { // __getstate__
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/* Return a tuple that fully encodes the state of the object */
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@ -329,9 +329,6 @@ class Tensor : public MetaTensor {
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// It is different from 'operator==' which just compare shape/type/address, it do real value comparison.
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bool ValueEqual(const Tensor &other) const;
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// It is different from 'operator==' which just compare shape/type/address, it do real value comparison.
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bool ValueEqualPy(const py::object &other) const;
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bool operator==(const Value &other) const override {
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if (other.isa<Tensor>()) {
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auto other_ = static_cast<const Tensor &>(other);
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@ -74,6 +74,17 @@ class Tensor(Tensor_):
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out = tensor_operator_registry.get('__add__')(self, other)
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return out
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def __eq__(self, other):
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if not isinstance(other, Tensor):
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return False
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x = self.asnumpy()
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y = other.asnumpy()
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out = np.equal(x, y)
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return Tensor(np.array(out))
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def __hash__(self):
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return hash(id(self))
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def __mul__(self, other):
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check_type('tensor input_data', other, (Tensor, float, int))
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out = tensor_operator_registry.get('__mul__')(self, other)
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@ -144,3 +144,5 @@ stop_gradient = Primitive("stop_gradient")
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tensor_operator_registry.register('__add__', tensor_add)
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tensor_operator_registry.register('__mul__', tensor_mul)
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tensor_operator_registry.register('__div__', tensor_div)
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#ms cannot support Tensor(True) compare
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tensor_operator_registry.register('__eq__', equal)
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@ -172,7 +172,7 @@ def vm_impl_equal(self):
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x = x.asnumpy()
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y = y.asnumpy()
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out = vm.equal(x, y)
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return Tensor(out)
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return Tensor(np.array(out))
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return vm_impl
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@ -183,7 +183,7 @@ def vm_impl_not_equal(self):
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x = x.asnumpy()
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y = y.asnumpy()
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out = vm.not_equal(x, y)
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return Tensor(out)
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return Tensor(np.array(out))
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return vm_impl
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@ -194,7 +194,7 @@ def vm_impl_greater(self):
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x = x.asnumpy()
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y = y.asnumpy()
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out = vm.greater(x, y)
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return Tensor(out)
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return Tensor(np.array(out))
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return vm_impl
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@vm_impl_getters.register(P.Maximum)
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@ -219,17 +219,17 @@ def vm_impl_minimum(self):
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return vm_impl
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@vm_impl_getters.register(P.Less)
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def vm_impl_greater(self):
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def vm_impl_less(self):
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"""Generate vm_impl function for Less"""
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def vm_impl(x, y):
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x = x.asnumpy()
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y = y.asnumpy()
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out = vm.less(x, y)
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return Tensor(out)
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return Tensor(np.array(out))
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return vm_impl
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@vm_impl_getters.register(P.ScalarCast)
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def vm_impl_greater(self):
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def vm_impl_scalar_cast(self):
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"""Generate vm_impl function for ScalarCast"""
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def vm_impl(x, t):
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np_type = dtype_to_nptype(t)
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