- 08 8月, 2017 1 次提交
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由 Yan Chunwei 提交于
* fix some enforce * remove compatible_type to avoid compile error * remove shared_ptr * fix tensor error msg
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- 28 7月, 2017 1 次提交
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由 qijun 提交于
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- 26 7月, 2017 1 次提交
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由 liaogang 提交于
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- 25 7月, 2017 2 次提交
- 19 7月, 2017 1 次提交
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由 fengjiayi 提交于
ATTENTION: some interfaces changed: 1. void Tensor::set_dims(const DDim& dims) ==> void Tensor::Resize(const DDim& dims). 2. void Tensor::ShareDataFrom(const Tensor& src) ==> void Tensor::ShareDataWith(const Tensor& src) 3. DDim Tensor::dims() const ==> const DDim& Tensor::dims() const
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- 15 7月, 2017 4 次提交
- 14 7月, 2017 2 次提交
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由 fengjiayi 提交于
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由 fengjiayi 提交于
1. Add template T which indicates data type to `CopyFrom()`, `Slice()` and `ShareData()` functions. This makes `CopyData()` code much clearer. 2. Add `set_dim()`. 3. `product(DDim)` transforms `DDim` to `vector<int>` first and then calculate its product. That might be quite slow. For `product(dims_)` is frequently used in Tensor, we add a mumber variable `numel_` as a cache of the product result. TODO: refactor `product()` to make it more efficient. 4. Unable Tensor::operator= 5. Remove the limit of POD type, because `float16` and `int8` are not POD type.
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- 12 7月, 2017 1 次提交
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由 fengjiayi 提交于
1. Add `Tensor::CopyFrom`. Current version can only support CPU memory copy. The support of GPU will be provided later by `paddle::memory`. The current implementation of `Tensor::CopyFrom` is a little inefficient: Every time `CopyFrom` is called, tensor will re-allocate its memory. However, if we try to check and reuse `placeholder_`, we have to provide a template parameter for `CopyFrom` to indicate the data type. It seems strange for a simple copy function. 2. Add `Tensor::mutable_data(Place place)`, which directly use member variable `dims_` as its dim parameter. This interface is required by `Op::InferShape`.
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- 11 7月, 2017 1 次提交
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由 fengjiayi 提交于
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- 03 7月, 2017 3 次提交