From 5d71ca72247405eaa8fc3af04c9e6ccb06a92645 Mon Sep 17 00:00:00 2001 From: salvacarrion Date: Wed, 24 Feb 2021 16:23:51 +0100 Subject: [PATCH 1/5] Minor change --- docs/markdown/eddl_progress.md | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/docs/markdown/eddl_progress.md b/docs/markdown/eddl_progress.md index 90371fe1f..593d3f5c6 100644 --- a/docs/markdown/eddl_progress.md +++ b/docs/markdown/eddl_progress.md @@ -4,7 +4,7 @@ | ----- |---------| | 🟢️ | Done | | 🔴️ | Todo | -| 🔴️ | Not planned | +| ⚫️ | Not planned / Not supported | # Layers --- @@ -34,7 +34,7 @@ | HardSigmoid | 🟢️️ | 🟢️️ | 🟢️️ | Hard sigmoid activation function. | | LeakyReLu | 🟢️️ | 🟢️️ | 🟢️️ | Leaky version of a Rectified Linear Unit. | | Linear | 🟢️️ | 🟢️️ | 🟢️️ (Custom Op) | Linear (i.e. identity) activation function. | -| PReLU | 🔴️ | 🔴️ | 🔴️ | Parametric Rectified Linear Unit. | +| PReLU | ⚫️️ | ⚫️ | ⚫️️ | Parametric Rectified Linear Unit. | | ReLu | 🟢️️ | 🟢️️ | 🟢️️ | Rectified Linear Unit. | | Softmax | 🟢️️ | 🟢️️ | 🟢️️ | Softmax activation function. | | Selu | 🟢️️ | 🟢️️ | 🟢️️ | Scaled Exponential Linear Unit (SELU). | @@ -51,7 +51,7 @@ | ------------- |------| -----| ------|---------| | Conv1D | 🟢️️ | 🟢️️ | 🟢️️ | 1D convolution. | | Conv2D | 🟢️️ | 🟢️️ | 🟢️️ | 2D convolution. | -| Conv3D | 🔴️ | 🔴️ | 🔴️ | 3D convolution. | +| Conv3D | 🔴 | 🔴️ | 🔴️ | 3D convolution. | | Pointwise | 🟢️️ | 🟢️️ | 🟢️️ | 2D pointwise convolution. | | DepthwiseConv2D | 🔴️ | 🔴️ | 🔴️ | 2D depthsise convolution. | | TransposedConv2D | 🔴️ | 🔴️ | 🔴️ | Transposed convolution | @@ -66,9 +66,9 @@ Deterministic transformations | Functionality | CPU | GPU | ONNX | Comments | | ------------- |------| -----| ------|---------| -| Crop | 🟢️️ | 🟢️️ | 🔴️ | Crops the given image at `[(top, left), (bottom, right)]` | -| CenteredCrop | 🟢️️ | 🟢️️ | 🔴️ | Crops the given image at the center with size (width, height) | -| ColorJitter | 🔴️ | 🔴️ | 🔴️ | Randomly change the brightness, contrast and saturation of an image. | +| Crop | 🟢️️ | 🟢️️ | ⚫️️ | Crops the given image at `[(top, left), (bottom, right)]` | +| CenteredCrop | 🟢️️ | 🟢️️ | ⚫️ | Crops the given image at the center with size (width, height) | +| ColorJitter | ⚫️ | ⚫️️ | ⚫️ | Randomly change the brightness, contrast and saturation of an image. | | CropScale | 🟢️️ | 🟢️️ | 🔴️ | Crop the given image at `[(top, left), (bottom, right)]` and scale it to the parent size | | Cutout | 🟢️️ | 🟢️️ | 🔴️ | Selects a rectangle region in an image at `[(top, left), (bottom, right)]` and erases its pixels using a constant value. | | Flip | 🟢️️ | 🟢️️ | 🔴️ | Flip the given image at `axis=n`. | @@ -88,17 +88,17 @@ Apply data transformations with random parametrization. | Functionality | CPU | GPU | ONNX | Comments | | ------------- |------| -----| ------|---------| -| RandomAffine | 🔴️ | 🔴️ | 🔴️ | Random affine transformation of the image keeping center invariant: rotate+translate+scale+shear | -| RandomCrop | 🟢️️ | 🟢️️ | 🔴️ | Crop the given image at a random location with size `[height, width]` | -| RandomCropScale | 🟢️️ | 🟢️️ | 🔴️ | Crop the given image randomly by the size in a range `[a, b]` by and scale it to the parent size | -| RandomCutout | 🟢️️ | 🟢️️ | 🔴️ | Randomly selects a rectangle region in an image and erases its pixels. The random region is defined by the range `[(min_x, max_x), (min_y, max_y)]`, where these are relative values | -| RandomFlip | 🟢️️ | 🟢️️ | 🔴️ | Flip the given image at `axis=n` randomly with a given probability. | -| RandomGrayscale | 🔴 | 🔴 | 🔴️ | Randomly convert image to grayscale with a probability of p (default 0.1). | -| RandomHorizontalFlip | 🟢️️ | 🟢️️ | 🔴️ | Horizontally flip the given image randomly with a given probability. | -| RandomRotation | 🟢️️ | 🟢️️ | 🔴️ | Rotate the image randomly by an angle defined in a range `[a, b]`. | -| RandomScale | 🟢️️ | 🟢️️ | 🔴️ | Resize the input image randomly by the size in a range `[a, b]` | -| RandomShift | 🟢️️ | 🟢️️ | 🔴️ | Shift the input image randomly in range `[a, b]` | -| RandomVerticalFlip | 🟢️️ | 🟢️️ | 🔴️ | Vertically flip the given image randomly with a given probability. | +| RandomAffine | 🔴️ | ⚫️ | ⚫️ | Random affine transformation of the image keeping center invariant: rotate+translate+scale+shear | +| RandomCrop | 🟢️️ | 🟢️️ | ⚫️ | Crop the given image at a random location with size `[height, width]` | +| RandomCropScale | 🟢️️ | 🟢️️ | ⚫️ | Crop the given image randomly by the size in a range `[a, b]` by and scale it to the parent size | +| RandomCutout | 🟢️️ | 🟢️️ | ⚫️ | Randomly selects a rectangle region in an image and erases its pixels. The random region is defined by the range `[(min_x, max_x), (min_y, max_y)]`, where these are relative values | +| RandomFlip | 🟢️️ | 🟢️️ | ⚫️ | Flip the given image at `axis=n` randomly with a given probability. | +| RandomGrayscale | 🔴 | 🔴 | ⚫️ | Randomly convert image to grayscale with a probability of p (default 0.1). | +| RandomHorizontalFlip | 🟢️️ | 🟢️️ | ⚫️ | Horizontally flip the given image randomly with a given probability. | +| RandomRotation | 🟢️️ | 🟢️️ | ⚫️ | Rotate the image randomly by an angle defined in a range `[a, b]`. | +| RandomScale | 🟢️️ | 🟢️️ | ⚫️ | Resize the input image randomly by the size in a range `[a, b]` | +| RandomShift | 🟢️️ | 🟢️️ | ⚫️ | Shift the input image randomly in range `[a, b]` | +| RandomVerticalFlip | 🟢️️ | 🟢️️ | ⚫️ | Vertically flip the given image randomly with a given probability. | ## Merge layers From 6cd89088e76bcda616e98d2acd172852c56929b8 Mon Sep 17 00:00:00 2001 From: salvacarrion Date: Wed, 24 Feb 2021 16:27:39 +0100 Subject: [PATCH 2/5] Minor changes --- docs/markdown/eddl_progress.md | 78 +++++++++++++++++----------------- 1 file changed, 39 insertions(+), 39 deletions(-) diff --git a/docs/markdown/eddl_progress.md b/docs/markdown/eddl_progress.md index 593d3f5c6..f7edebe08 100644 --- a/docs/markdown/eddl_progress.md +++ b/docs/markdown/eddl_progress.md @@ -18,8 +18,8 @@ | Flatten | 🟢️️ | 🟢️️ | 🟢️️ | Flattens the input. Does not affect the batch size. (Wrapper for Reshape) | | Input | 🟢️️ | 🟢️️ | 🟢️️ | Used to instantiate a EDDL tensor. | | Reshape | 🟢️️ | 🟢️️ | 🟢️️ | Reshapes an output to a certain shape. | -| Squeeze | 🟢️️ | 🟢️️ | 🔴️ | Reshapes an output to a certain shape. | -| Unsqueeze | 🟢️️ | 🟢️️ | 🔴️ | Reshapes an output to a certain shape. | +| Squeeze | 🟢️️ | 🟢️️ | ⚫️ | Reshapes an output to a certain shape. | +| Unsqueeze | 🟢️️ | 🟢️️ | ⚫️ | 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]]` | | Transpose | 🟢️️ | 🟢️️ | ️🟢️️ | Permute the last two dimensions | @@ -69,17 +69,17 @@ Deterministic transformations | Crop | 🟢️️ | 🟢️️ | ⚫️️ | Crops the given image at `[(top, left), (bottom, right)]` | | CenteredCrop | 🟢️️ | 🟢️️ | ⚫️ | Crops the given image at the center with size (width, height) | | ColorJitter | ⚫️ | ⚫️️ | ⚫️ | Randomly change the brightness, contrast and saturation of an image. | -| CropScale | 🟢️️ | 🟢️️ | 🔴️ | Crop the given image at `[(top, left), (bottom, right)]` and scale it to the parent size | -| Cutout | 🟢️️ | 🟢️️ | 🔴️ | Selects a rectangle region in an image at `[(top, left), (bottom, right)]` and erases its pixels using a constant value. | -| Flip | 🟢️️ | 🟢️️ | 🔴️ | Flip the given image at `axis=n`. | -| Grayscale | 🔴️ | 🔴️ | 🔴️️ | Convert image to grayscale. | -| HorizontalFlip | 🟢️️ | 🟢️️ | 🔴️ | Horizontally flip the given image. | -| Pad | 🔴️ | 🔴️ | 🔴️ | Pad the given image on all sides with the given "pad" value. | -| Rotate | 🟢️️ | 🟢️️ | 🔴️ | Rotate the image by angle. | -| Scale | 🟢️️ | 🟢️️ | 🔴️ | Resize the input image to the given size. `[height, width]` | -| Shift | 🟢️️ | 🟢️️ | 🔴️ | Shift the input image `[a, b]` | -| VerticallyFlip | 🟢️️ | 🟢️️ | 🔴️ | Vertically flip the given image. | -| Normalize | 🔴 | 🔴️ | 🔴️ | Normalize an image with mean and standard deviation. | +| CropScale | 🟢️️ | 🟢️️ | ⚫️ | Crop the given image at `[(top, left), (bottom, right)]` and scale it to the parent size | +| Cutout | 🟢️️ | 🟢️️ | ⚫️ | Selects a rectangle region in an image at `[(top, left), (bottom, right)]` and erases its pixels using a constant value. | +| Flip | 🟢️️ | 🟢️️ | ⚫️ | Flip the given image at `axis=n`. | +| Grayscale | ⚫️ | ⚫️ | ⚫️️ | Convert image to grayscale. | +| HorizontalFlip | 🟢️️ | 🟢️️ | ⚫️ | Horizontally flip the given image. | +| Pad | ⚫️ | ⚫️ | ⚫️ | Pad the given image on all sides with the given "pad" value. | +| Rotate | 🟢️️ | 🟢️️ | ⚫️ | Rotate the image by angle. | +| Scale | 🟢️️ | 🟢️️ | ⚫️ | Resize the input image to the given size. `[height, width]` | +| Shift | 🟢️️ | 🟢️️ | ⚫️ | Shift the input image `[a, b]` | +| VerticallyFlip | 🟢️️ | 🟢️️ | ⚫️ | Vertically flip the given image. | +| Normalize | ⚫ | ⚫️ | ⚫️ | Normalize an image with mean and standard deviation. | ### Data augmentations @@ -88,12 +88,12 @@ Apply data transformations with random parametrization. | Functionality | CPU | GPU | ONNX | Comments | | ------------- |------| -----| ------|---------| -| RandomAffine | 🔴️ | ⚫️ | ⚫️ | Random affine transformation of the image keeping center invariant: rotate+translate+scale+shear | +| RandomAffine | ⚫️ | ⚫️ | ⚫️ | Random affine transformation of the image keeping center invariant: rotate+translate+scale+shear | | RandomCrop | 🟢️️ | 🟢️️ | ⚫️ | Crop the given image at a random location with size `[height, width]` | | RandomCropScale | 🟢️️ | 🟢️️ | ⚫️ | Crop the given image randomly by the size in a range `[a, b]` by and scale it to the parent size | | RandomCutout | 🟢️️ | 🟢️️ | ⚫️ | Randomly selects a rectangle region in an image and erases its pixels. The random region is defined by the range `[(min_x, max_x), (min_y, max_y)]`, where these are relative values | | RandomFlip | 🟢️️ | 🟢️️ | ⚫️ | Flip the given image at `axis=n` randomly with a given probability. | -| RandomGrayscale | 🔴 | 🔴 | ⚫️ | Randomly convert image to grayscale with a probability of p (default 0.1). | +| RandomGrayscale | ⚫ | ⚫ | ⚫️ | Randomly convert image to grayscale with a probability of p (default 0.1). | | RandomHorizontalFlip | 🟢️️ | 🟢️️ | ⚫️ | Horizontally flip the given image randomly with a given probability. | | RandomRotation | 🟢️️ | 🟢️️ | ⚫️ | Rotate the image randomly by an angle defined in a range `[a, b]`. | | RandomScale | 🟢️️ | 🟢️️ | ⚫️ | Resize the input image randomly by the size in a range `[a, b]` | @@ -120,19 +120,19 @@ Apply data transformations with random parametrization. | Functionality | CPU | GPU | ONNX | Comments | | ------------- |------| -----| ------|---------| | BatchNormalization | 🟢️️ | 🟢️️ | 🟢️️ | Batch normalization layer (Ioffe and Szegedy, 2014). | -| LayerNormalization | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | Layer normalization layer (Ba et al., 2016) | -| GroupNormalization | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | Group normalization layer (Yuxin Wu and Kaiming He, 2018). | -| Norm | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | -| NormMax | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | -| NormMinMax | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | +| LayerNormalization | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | Layer normalization layer (Ba et al., 2016) | +| GroupNormalization | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | Group normalization layer (Yuxin Wu and Kaiming He, 2018). | +| Norm | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | +| NormMax | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | +| NormMinMax | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | ## Noise layers | Functionality | CPU | GPU | ONNX | Comments | | ------------- |------| -----| ------|---------| -| GaussianNoise | 🟢️️ | 🟢️️ |🔴️ (Not in ONNX) | Apply additive zero-centered Gaussian noise. | -| UniformNoise | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | Apply additive zero-centered uniform noise. +| GaussianNoise | 🟢️️ | 🟢️️ |⚫ (Not in ONNX) | Apply additive zero-centered Gaussian noise. | +| UniformNoise | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | Apply additive zero-centered uniform noise. ## Pooling layers @@ -162,11 +162,11 @@ Apply data transformations with random parametrization. | Div | 🟢️️ | 🟢️️ | 🟢️️ | | | Exp | 🟢️️ | 🟢️️ | 🟢️️ | | | Log | 🟢️️ | 🟢️️ | 🟢️️ | | -| Log2 | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | -| Log10 | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | +| Log2 | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | +| Log10 | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | | Mult | 🟢️️ | 🟢️️ | 🟢️️ | | | Pow | 🔴️ | 🔴️ | 🔴️ | | -| Select | 🟢️️ | 🟢️️ | 🔴️ (Not in ONNX) | | +| Select | 🟢️️ | 🟢️️ | ⚫ (Not in ONNX) | | | Sqrt | 🟢️️ | 🟢️️ | 🟢️️ | | | Sub | 🟢️️ | 🟢️️ | 🟢️️ | | @@ -179,7 +179,7 @@ Apply data transformations with random parametrization. | Mean | 🟢️️| 🟢️️ | 🟢️️ | | | Min | 🟢️️| 🟢️️ | 🟢️️ | | | Sum | 🟢️️| 🟢️️ | 🟢️️ | | -| Var | 🟢️️| 🟢️️ | 🔴️ (Not in ONNX) | | +| Var | 🟢️️| 🟢️️ | ⚫ (Not in ONNX) | | | Argmax | 🟢️️| 🟢️️ | 🟢️️ | | @@ -210,24 +210,24 @@ Apply data transformations with random parametrization. | GlorotUniform | 🟢️️ | 🟢️️ | Glorot uniform initializer, also called Xavier uniform initializer. | | HeNormal | 🟢️️ | 🟢️️ | _He_ normal initializer. | | HeUniform | 🟢️️ | 🟢️️ | _He_ uniform initializer. | -| Identity | 🔴️ | 🔴️ | Initializer that generates the identity matrix. | -| LeCunUniform | 🔴 | 🔴 | LeCun uniform initializer. | -| LeCunNormal | 🔴 | 🔴 | LeCun normal initializer. | -| Orthogonal | 🔴️| 🔴 | Initializer that generates a random orthogonal matrix. | +| Identity | ⚫️ | ⚫️ | Initializer that generates the identity matrix. | +| LeCunUniform | ⚫ | ⚫ | LeCun uniform initializer. | +| LeCunNormal | ⚫ | ⚫ | LeCun normal initializer. | +| Orthogonal | ⚫️| ⚫ | Initializer that generates a random orthogonal matrix. | | RandomNormal | 🟢️️ | 🟢️️ | Initializer that generates tensors with a normal distribution. | | RandomUniform | 🟢️️ | 🟢️️ | Initializer that generates tensors with a uniform distribution. | -| TruncatedNormal | 🔴 | 🔴 | Initializer that generates a truncated normal distribution. | -| VarianceScaling | 🔴 | 🔴️ | Initializer capable of adapting its scale to the shape of weights. | +| TruncatedNormal | ⚫ | ⚫ | Initializer that generates a truncated normal distribution. | +| VarianceScaling | ⚫ | ⚫️ | Initializer capable of adapting its scale to the shape of weights. | # Constraints | Functionality | CPU | GPU | Comments | | ------------- |------| -----|---------| -| MaxNorm | 🔴️ | 🔴️ | MaxNorm weight constraint. | -| MinMaxNorm | 🔴️ | 🔴️ | MinMaxNorm weight constraint. | -| NonNeg | 🔴️ | 🔴️ | Constrains the weights to be non-negative. | -| UnitNorm | 🔴️ | 🔴️ | Constrains the weights incident to each hidden unit to have unit norm. | +| MaxNorm | ⚫️ | ⚫️️ | MaxNorm weight constraint. | +| MinMaxNorm | ⚫️ | ⚫️️ | MinMaxNorm weight constraint. | +| NonNeg | ⚫️ | ⚫️️ | Constrains the weights to be non-negative. | +| UnitNorm | ⚫️ | ⚫️️ | Constrains the weights incident to each hidden unit to have unit norm. | # Loss functions @@ -241,7 +241,7 @@ Apply data transformations with random parametrization. | MRE | 🔴️ | 🔴️ | Mean Relative Error | | MSLE | 🔴️ | 🔴️ | Mean Squared Logarithmic Error | | Min | 🟢️️ | 🟢️️ | Minimum Error | -| Hinge | 🔴️ | 🔴️ | Hinge Error | +| Hinge | ⚫ | ⚫ | Hinge Error | | Dice | 🟢️️ | 🟢️️ | Dice loss | | SoftCrossEntropy | 🟢️️ | 🟢️️ | Soft-Categorical Cross-Entropy Error | @@ -251,8 +251,8 @@ Apply data transformations with random parametrization. | Functionality | CPU | GPU | Comments | | ------------- |------| -----|---------| | CategoricalAccuracy | 🟢️️ | 🟢️️ | | -| TopKAccuracy | 🔴️ | 🔴 | | -| CosineProximity | 🔴️ | 🔴️ | | +| TopKAccuracy | ⚫ | ⚫ | | +| CosineProximity | ⚫ | ⚫ | | | MSE | 🟢️️ | 🟢️️ | Mean Squared Error | | MAE | 🟢️️ | 🟢️️ | Mean Absolute Error | | MRE | 🟢️️ | 🟢️️ | Mean Relative Error | From 495360892c3dcaf8558261b2d5a1e008c0937551 Mon Sep 17 00:00:00 2001 From: salvacarrion Date: Wed, 24 Feb 2021 16:32:05 +0100 Subject: [PATCH 3/5] Update formulas --- formulas/brew/eddl.rb | 4 ++-- formulas/conda/eddl/build.sh | 4 ++-- formulas/conda/eddl/meta.yaml | 6 +++--- 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/formulas/brew/eddl.rb b/formulas/brew/eddl.rb index e5b4eaafd..c120d0de6 100644 --- a/formulas/brew/eddl.rb +++ b/formulas/brew/eddl.rb @@ -4,8 +4,8 @@ class Eddl < Formula desc "European Distributed Deep Learning Library (EDDL)" homepage "https://github.com/deephealthproject/eddl" - url "https://github.com/deephealthproject/eddl/archive/v0.9a.tar.gz" - sha256 "93372aca9133f847c9dd2dd678a2107e9424d512e806929065fbe2a17270a425" + url "https://github.com/deephealthproject/eddl/archive/v0.9.1b.tar.gz" + sha256 "a486d699036feb893bfd95e60405ddf8d3cd9f3e4eabb61f3e65b1b7e01a1139" depends_on "cmake" => :build depends_on "eigen" => :build diff --git a/formulas/conda/eddl/build.sh b/formulas/conda/eddl/build.sh index ad05725b9..5bf8c65c6 100644 --- a/formulas/conda/eddl/build.sh +++ b/formulas/conda/eddl/build.sh @@ -29,8 +29,8 @@ echo "CPU_COUNT=$CPU_COUNT" echo "#################################################" # Build makefiles -cmake -DBUILD_TARGET=CPU \ - -DBUILD_SUPERBUILD=OFF \ +cmake -DBUILD_TARGET=CUDNN \ + -DBUILD_SUPERBUILD=ON \ -DBUILD_EXAMPLES=OFF \ -DBUILD_TESTS=OFF \ -DCMAKE_C_COMPILER=$CC \ diff --git a/formulas/conda/eddl/meta.yaml b/formulas/conda/eddl/meta.yaml index 17882ea28..a0282ebba 100644 --- a/formulas/conda/eddl/meta.yaml +++ b/formulas/conda/eddl/meta.yaml @@ -1,6 +1,6 @@ -{% set name = "eddl-cpu" %} # If this is a package for GPU, use: "eddl-gpu" -{% set version = "0.9a" %} -{% set sha256 = "93372aca9133f847c9dd2dd678a2107e9424d512e806929065fbe2a17270a425" %} +{% set name = "eddl-cudnn" %} # If this is a package for GPU, use: "eddl-gpu" +{% set version = "0.9.1b" %} +{% set sha256 = "a486d699036feb893bfd95e60405ddf8d3cd9f3e4eabb61f3e65b1b7e01a1139" %} package: name: {{ name|lower }} From c6156c2de82bff2259c3286d663f02fb02c4cdeb Mon Sep 17 00:00:00 2001 From: salvacarrion Date: Wed, 24 Feb 2021 16:32:28 +0100 Subject: [PATCH 4/5] Add numpy section to troubleshoot.rst --- docs/sphinx/source/intro/troubleshoot.rst | 30 +++++++++++++++++++++++ 1 file changed, 30 insertions(+) diff --git a/docs/sphinx/source/intro/troubleshoot.rst b/docs/sphinx/source/intro/troubleshoot.rst index 45405b0ca..3588c9be7 100644 --- a/docs/sphinx/source/intro/troubleshoot.rst +++ b/docs/sphinx/source/intro/troubleshoot.rst @@ -311,3 +311,33 @@ If you want to run it using the conda environment, add: echo $CONDA_PREFIX .. _more: https://stackoverflow.com/questions/39979836/using-openmp-with-c11-on-mac-os + + +Loading datasets +----------------- + +Loading a Numpy file (.npy) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Currently, we cannot do this natively from the EDDL. However, you can do it with the PyEDDL. + +First, install Numpy and the PyEDDL in you environment: + +.. code:: bash + + pip install numpy + conda install -c dhealth pyeddl-cpu # or *-gpu + +Then, we need to create a python file (``test.py``) in order to read the numpy file and convert it to ``.bin``: + +.. code:: python + + from pyeddl.tensor import Tensor + import numpy as np + + # Convert numpy to bin + t_npy = np.load("myarray.npy") + t_eddl = Tensor.fromarray(t_npy) + t_eddl.save("myarray.bin") + + From ba74e28c183d6b3d73b14187fb2a255d9ea3bbbf Mon Sep 17 00:00:00 2001 From: salvacarrion Date: Wed, 24 Feb 2021 16:49:35 +0100 Subject: [PATCH 5/5] Minor changes (formulas, docs) --- docs/sphinx/source/intro/troubleshoot.rst | 2 +- formulas/brew/eddl.rb | 4 ++-- formulas/conda/eddl/build.sh | 4 ++-- formulas/conda/eddl/meta.yaml | 2 +- 4 files changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/sphinx/source/intro/troubleshoot.rst b/docs/sphinx/source/intro/troubleshoot.rst index 3588c9be7..90698497e 100644 --- a/docs/sphinx/source/intro/troubleshoot.rst +++ b/docs/sphinx/source/intro/troubleshoot.rst @@ -316,7 +316,7 @@ If you want to run it using the conda environment, add: Loading datasets ----------------- -Loading a Numpy file (.npy) +Loading Numpy files (.npy) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Currently, we cannot do this natively from the EDDL. However, you can do it with the PyEDDL. diff --git a/formulas/brew/eddl.rb b/formulas/brew/eddl.rb index c120d0de6..e6d93cf95 100644 --- a/formulas/brew/eddl.rb +++ b/formulas/brew/eddl.rb @@ -17,8 +17,8 @@ class Eddl < Formula def install mkdir "build" do - system "cmake", "..", "-DBUILD_SUPERBUILD=OFF", "-DBUILD_EXAMPLES=OFF", "-DBUILD_TESTS=OFF", *std_cmake_args - system "make", "install", "PREFIX=#{prefix}" + system "cmake", "..", "-DBUILD_SUPERBUILD=OFF", "-DBUILD_EXAMPLES=OFF", "-DBUILD_TESTS=OFF", "-DBUILD_OPENMP=OFF" *std_cmake_args + system "make", "-j", "install", "PREFIX=#{prefix}" end end diff --git a/formulas/conda/eddl/build.sh b/formulas/conda/eddl/build.sh index 5bf8c65c6..ad05725b9 100644 --- a/formulas/conda/eddl/build.sh +++ b/formulas/conda/eddl/build.sh @@ -29,8 +29,8 @@ echo "CPU_COUNT=$CPU_COUNT" echo "#################################################" # Build makefiles -cmake -DBUILD_TARGET=CUDNN \ - -DBUILD_SUPERBUILD=ON \ +cmake -DBUILD_TARGET=CPU \ + -DBUILD_SUPERBUILD=OFF \ -DBUILD_EXAMPLES=OFF \ -DBUILD_TESTS=OFF \ -DCMAKE_C_COMPILER=$CC \ diff --git a/formulas/conda/eddl/meta.yaml b/formulas/conda/eddl/meta.yaml index a0282ebba..0320f536c 100644 --- a/formulas/conda/eddl/meta.yaml +++ b/formulas/conda/eddl/meta.yaml @@ -1,4 +1,4 @@ -{% set name = "eddl-cudnn" %} # If this is a package for GPU, use: "eddl-gpu" +{% set name = "eddl-cpu" %} # If this is a package for GPU, use: "eddl-gpu" {% set version = "0.9.1b" %} {% set sha256 = "a486d699036feb893bfd95e60405ddf8d3cd9f3e4eabb61f3e65b1b7e01a1139" %}