Merge branch 'master' of https://github.com/deephealthproject/eddl

docs/markdown/eddl_progress.md

@@ -19,7 +19,7 @@
 | Input | ✔️ | ✔️ | ✔️ | Used to instantiate a EDDL tensor. |
 | Reshape | ✔️ | ✔️ | ✔️ | Reshapes an output to a certain shape. |
 | Permute | ✔️ | ✔️ | ✔️  | Permutes the dimensions of the input according to a given pattern. |
-| Embedding | ❌️ | ❌️ | ❌️ | Turns positive integers (indexes) into dense vectors of fixed size; (also known as mapping). e.g. `[[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]]` |
+| Embedding | ✔️ | ✔️ | ❌️ | Turns positive integers (indexes) into dense vectors of fixed size; (also known as mapping). e.g. `[[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]]` |
 | Transpose | ✔️ | ✔️ | ❌️ | Permute the last two dimensions |
 
 
@@ -174,8 +174,8 @@ Apply data transformations with random parametrization.
 | Functionality | CPU | GPU | ONNX | Comments |
 | ------------- |------| -----| ------|---------|
 | GRU | ❌️ | ❌️ | ❌️ | Gated Recurrent Unit - Cho et al. 2014. |
-| LSTM | ❌️ | ❌️ | ❌️ | Long Short-Term Memory layer - Hochreiter 1997. |
-| RNN | ❌️ | ❌️ | ❌️ | Fully-connected RNN where the output is to be fed back to input. |
+| LSTM | ✔️ | ✔️  | ❌️ | Long Short-Term Memory layer - Hochreiter 1997. |
+| RNN | ✔️ | ✔️  | ❌️ | Fully-connected RNN where the output is to be fed back to input. |
 
 
 ## Regularizer layers
@@ -227,6 +227,7 @@ Apply data transformations with random parametrization.
 | MSLE | ❌️ | ❌️ | Mean Squared Logarithmic Error |
 | Min | ✔️ | ✔️ | Minimum Error |
 | Hinge | ❌️ | ❌️ | Hinge Error |
+| Dice  | ✔️ | ✔️  | Dice loss |
 | SoftCrossEntropy | ✔️ | ✔️ | Soft-Categorical Cross-Entropy Error |
 
 
@@ -241,6 +242,7 @@ Apply data transformations with random parametrization.
 | MAE | ✔️ | ✔️ | Mean Absolute Error  |
 | MRE | ✔️ | ✔️ | Mean Relative Error |
 | Sum | ✔️ | ✔️ | Sum Error |
+| Dice  | ✔️ | ✔️  | Dice error |
 
 
 # Optimizers