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bulk change type T to type *T* in spec (#6486)

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* bulk change `type T` to `type *T*` in spec

* update all `T` which referee to type to use *T* pattern

* get back with `T` where T is dimension

* fix *T*1 -> *T1*

* Make italic types where was no formating
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Patryk Elszkowski authored and GitHub committed 2021-07-02 13:51:00 +03:00
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docs/ops/image/Interpolate_4.md
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@@ -89,13 +89,13 @@
**Inputs**
* **1**: `data` - tensor of type `T` with data for interpolation. **Required.**
* **1**: `data` - tensor of type *T* with data for interpolation. **Required.**
* **2**: `sizes` - 1D tensor of type `T_SIZE` describing output shape for spatial axes. Number of elements matches the number of indices in `axes` input, the order matches as well. **Required.**
* **2**: `sizes` - 1D tensor of type *T_SIZE* describing output shape for spatial axes. Number of elements matches the number of indices in `axes` input, the order matches as well. **Required.**
* **3**: `scales` - 1D tensor of type `T_SCALES` describing scales for spatial axes. Number and order of elements match the number and order of indices in `axes` input. **Required.**
* **3**: `scales` - 1D tensor of type *T_SCALES* describing scales for spatial axes. Number and order of elements match the number and order of indices in `axes` input. **Required.**
* **4**: `axes` - 1D tensor of type `T_AXES` specifying dimension indices where interpolation is applied, and `axes` is any unordered list of indices of different dimensions of input tensor, e.g. `[0, 4]`, `[4, 0]`, `[4, 2, 1]`, `[1, 2, 3]`. These indices should be non-negative integers from `0` to `rank(data) - 1` inclusively. Other dimensions do not change. The order of elements in `axes` attribute matters, and mapped directly to elements in the 2nd input `sizes`. **Optional** with default value `[0,...,rank(data) - 1]`.
* **4**: `axes` - 1D tensor of type *T_AXES* specifying dimension indices where interpolation is applied, and `axes` is any unordered list of indices of different dimensions of input tensor, e.g. `[0, 4]`, `[4, 0]`, `[4, 2, 1]`, `[1, 2, 3]`. These indices should be non-negative integers from `0` to `rank(data) - 1` inclusively. Other dimensions do not change. The order of elements in `axes` attribute matters, and mapped directly to elements in the 2nd input `sizes`. **Optional** with default value `[0,...,rank(data) - 1]`.
**Outputs**