mirror of https://github.com/llvm/torch-mlir
e57d3f9774
- This commit adds E2E support for `aten.rand_like` and `aten.bernoulli_.Tensor` ops. - The `aten.bernoulli(x)` was implemented as: `aten.bernoulli(x) = rand_like(x) < 0.5`, assuming 0.5 as default probability, whereas according to the pytorch documentation: https://pytorch.org/docs/stable/generated/torch.bernoulli.html#torch.bernoulli the input x in `aten.bernoulli(x)` is itself a tensor containing probabilities to be used for drawing the binary random number. - So this commit fixes the `aten.bernoulli(x)` implementation as: `aten.bernoulli(x) = rand_like(x) < x`. - It also fixes the case where the input to `aten.bernoulli_.float` is an integer tensor. In this case the input must be casted to float type before passing it as operand to `aten.rand_like` op. `aten.bernoulli_.float(x, p) = rand_like(float(x)) < p`. Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com> |
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| .. | ||
| GlobalizeObjectGraph | ||
| adjust-calling-conventions.mlir | ||
| canonicalize.mlir | ||
| decompose-complex-ops.mlir | ||
| inline-global-slots.mlir | ||
| invalid.mlir | ||
| maximize-value-semantics.mlir | ||
| ops.mlir | ||
| prepare-for-globalize-object-graph.mlir | ||
| promote-types.mlir | ||
| reduce-op-variants-error.mlir | ||
| reduce-op-variants.mlir | ||
| refine-public-return.mlir | ||
| refine-types-branch.mlir | ||
| refine-types.mlir | ||