()
| 6570 | this._has_init = false; |
| 6571 | } |
| 6572 | is_nondeterministic() { |
| 6573 | if (this._schema.name === 'aten::dropout' && this._schema.overload === '') { |
| 6574 | // |
| 6575 | } |
| 6576 | torch._C.nondeterministic_op_strings = torch._C.nondeterministic_op_strings || new Set([ |
| 6577 | 'aten::dropout(Tensor input, float p, bool train) -> Tensor', |
| 6578 | 'aten::_fused_dropout(Tensor self, float p, Generator? generator) -> (Tensor, Tensor)', |
| 6579 | 'aten::_standard_gamma(Tensor self, Generator? generator) -> Tensor', |
| 6580 | 'aten::bernoulli(Tensor self, *, Generator? generator) -> Tensor', |
| 6581 | 'aten::bernoulli(Tensor self, float p, *, Generator? generator) -> Tensor', |
| 6582 | 'aten::multinomial(Tensor self, int num_samples, bool replacement, *, Generator? generator) -> Tensor', |
| 6583 | 'aten::native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor)', |
| 6584 | 'aten::normal(Tensor mean, Tensor std, *, Generator? generator) -> Tensor', |
| 6585 | 'aten::normal(float mean, Tensor std, *, Generator? generator) -> Tensor', |
| 6586 | 'aten::normal(Tensor mean, float std, *, Generator? generator) -> Tensor', |
| 6587 | 'aten::poisson(Tensor self, Generator? generator) -> Tensor', |
| 6588 | 'aten::binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor', |
| 6589 | 'aten::rrelu(Tensor self, Scalar lower, Scalar upper, bool training, Generator? generator) -> Tensor', |
| 6590 | 'aten::rrelu_with_noise(Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, Generator? generator) -> Tensor', |
| 6591 | 'aten::rand(int[] size, *, int? dtype, int? layout, Device? device, bool? pin_memory) -> Tensor', |
| 6592 | 'aten::rand_like(Tensor self, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor', |
| 6593 | 'aten::randint(int high, int[] size, *, int? dtype, int? layout, Device? device, bool? pin_memory) -> Tensor', |
| 6594 | 'aten::randint(int low, int high, int[] size, *, int? dtype, int? layout, Device? device, bool? pin_memory) -> Tensor', |
| 6595 | 'aten::randint_like(Tensor self, int high, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor', |
| 6596 | 'aten::randint_like(Tensor self, int low, int high, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor', |
| 6597 | 'aten::randn(int[] size, *, int? dtype, int? layout, Device? device, bool? pin_memory) -> Tensor', |
| 6598 | 'aten::randn_like(Tensor self, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor', |
| 6599 | 'aten::randperm(int n, *, int? dtype, int? layout, Device? device, bool? pin_memory) -> Tensor' |
| 6600 | ]); |
| 6601 | if (torch._C.nondeterministic_op_strings.has(this._schema.__str__())) { |
| 6602 | return true; |
| 6603 | } |
| 6604 | /* |
| 6605 | const auto& op = c10::Dispatcher::singleton().findOp( |
| 6606 | c10::OperatorName(schema_.name(), schema_.overload_name())); |
| 6607 | return op && op->hasTag(at::Tag::nondeterministic_seeded); |
| 6608 | */ |
| 6609 | return false; |
| 6610 | } |
| 6611 | }); |
| 6612 | this.registerType('torch._C.OperatorRegistry', class { |
| 6613 | constructor() { |
no test coverage detected