Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20374
This test case now also tests that the argument type works correctly in kernels that
- don't return outputs
- return multiple outputs
Reviewed By: li-roy
Differential Revision: D15298233
fbshipit-source-id: 82ab9d81b55b4f9fb34d66a155cc426af8592e25
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20373
- Add support for Dict<Key, Value> arguments and returns to c10 operators
- Add support for std::unordered_map<Key, Value> to the legacy API (but not to c10 kernels)
Reviewed By: li-roy
Differential Revision: D15298235
fbshipit-source-id: 6d9793db1f12bea377f508a9b33a495ebe0bec18
Summary:
Add automatic translations for a few argument names that commonly differ between PyTorch and NumPy.
For now, they are as follows:
* `keepdim` -> `keepdims`
* `dim` -> `axis`
* `input` -> (any of `a`, `x`, `x1`)
* `other` -> `x2`
Basic examples:
```python
>>> t=torch.randn(10,10)
>>> torch.sum(x=t, axis=1)
tensor([ 0.5199, -0.3768, 4.3619, -0.9105, 1.1804, 1.0837, -0.9036, 0.2365,
1.1171, -0.0999])
```
```python
>>> torch.add(x1=5, x2=6)
tensor(11)
```
The additional overhead is zero when using traditional PyTorch argument names, and a few (usually 1) extra PyDict lookups when using NumPy argument names.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20451
Differential Revision: D15337521
Pulled By: umanwizard
fbshipit-source-id: 7a7d389786f4ccf5c86a14ecb2002c61730c51b5
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20020
Add shape inference for LearningRate op. The output (lr) should have similar shape with input (iteration), but not the same type (float vs int).
Reviewed By: un-disclosed
Differential Revision: D15112300
fbshipit-source-id: 09969aefa15172a6f3c70cd9b2548e3020da5d7a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20372
Implement a Dict type that allows us to abstract away from the concrete implementation used.
The API is similar to std::unordered_map, but behind the scenes we can switch to any map implementation we like. ska::flat_hash_map, google dense map, or any future map implementation with better performance.
Switching such an implementation choice does not have to break backwards compatibility of kernel code using the Dict type.
Reviewed By: zdevito
Differential Revision: D15298234
fbshipit-source-id: b5ad368a9e9516030805cd8f5f1b02e3986933c0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20463
Source file changes mostly involve ifdef'ing-out references to JIT code
from files that are part of Caffe2Go. Update Internal build scripts to
remove those files from our globs.
After this, changes to most of the JIT files should not trigger mobile CI.
Reviewed By: dzhulgakov
Differential Revision: D15329407
fbshipit-source-id: 48f614c6b028eef0a03ce5161d083a3e078b0412
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20021
Add shape inference for AtomicIter operator. The operator takes two blobs iteration and iter_mutex as input and outputs iteration, which should have the same type and shape as the input.
Reviewed By: un-disclosed
Differential Revision: D15111643
fbshipit-source-id: 0d06413305cc4c6257c0cfabf62fb874970803bc
Summary:
Moving functions from torch/nn/modules/activation.py to torch/nn/functional.py. For functions not implemented (_get_input_buffer and _set_input_buffer), a TODO is added.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20415
Differential Revision: D15318078
Pulled By: jamarshon
fbshipit-source-id: 5ca698e2913821442cf8609cc61ac8190496a3c6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20390
duc0 Ngo implemented observing floating point exceptions but there were a couple of places where we have "benign" floating point exceptions leading to false positives. This diff eliminates one source of such false positives, namely using _mm256_cvtph_ps and _mm256_cvtps_ph for partially uninitialized array for the remainder loop.
Reviewed By: hx89
Differential Revision: D15307358
fbshipit-source-id: 38f57dfdd90c70bc693292d2f9c33c7ba558e2c9
Summary:
Tagging along to changes in #20191 which added more support for types in the pickler
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20444
Pulled By: driazati
Differential Revision: D15321463
fbshipit-source-id: 985061bf5070a7d7bad58ea8db11d531f3d13e74
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20108
Add cpp runs for c2, hooked up via pybinds. Print output to terminal. This is not hooked up with the pep output yet because I'd like to verify the numbers first.
Note that this isn't quite the same mechanism as the pytorch cpp hookup, which uses cpp_python_extensions. If I can use the same mechanism to pull all the inputs for c2 through cpp and do FeedBlobs in cpp, then I'll switch to that.
Reviewed By: zheng-xq
Differential Revision: D15155976
fbshipit-source-id: 708079dacd3e19aacfe43d70c5e5bc54da2cf9e3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20321
First part of https://github.com/pytorch/pytorch/issues/20287
- Rename `AT_ASSERT` to `TORCH_INTERNAL_ASSERT`
- Make `TORCH_INTERNAL_ASSERT` work with variadic inputs
- Deprecated `AT_ASSERT` and `AT_ASSERTM`
- Rename `AT_CHECK` to `TORCH_CHECK`
- Make `TORCH_CHECK` give a better error message when no arguments are
provided
- Deprecate `AT_ERROR` in favor of `TORCH_CHECK(false, ...)`
- Deprecate `AT_INDEX_ERROR` in favor of `TORCH_CHECK_INDEX(false, ...)`
- Rename `AT_WARN` to `TORCH_WARN`
No use sites are changed; I'll work on that in follow up patches
(or disable the deprecation, if necessary.)
Differential Revision: D15278439
fbshipit-source-id: 7e0ed489d4e89e5f56b8ad7eafa72cb9a06065ee
Summary:
In https://github.com/pytorch/pytorch/pull/18223/files#diff-77a6f3462f2233b921d3042412fed6d3R178, we used `auto saved_version_ = data_.unsafeGetTensorImpl()->version_counter().current_version()` and then `new_data_impl_copy->set_version_counter(saved_version_)`, which actually doesn't preserve the original semantics that `var.set_data(tensor)` should keep `var`'s version counter object intact. This PR fixes the bug and adds test to make sure it doesn't happen again.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20391
Differential Revision: D15323430
Pulled By: yf225
fbshipit-source-id: e3ba49b51ec8ccecd51c80cb182387f74cfd2b2b
Summary:
As part of the Variable/Tensor merge, we allow passing Tensor with AutogradMeta into ATen ops, but we want to make sure they are not treated as Variables (i.e. their `is_variable()` is false). This PR makes the necessary change to make this work.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20392
Differential Revision: D15321899
Pulled By: yf225
fbshipit-source-id: c2ab09db73c63bd71ba2d8391095f4d6b4240a9a
