Differences

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--- eman2:install:condainstall [2025/06/14 22:46] – created steveludtke
+++ eman2:install:condainstall [2025/07/06 18:34] (current) – steveludtke
@@ Line 1: / Line 1: @@
-====== EMAN2 Installation ======
+====== EMAN2 (Binary) Installation ======
 For up-to-date binary installations you must use the instructions on this page. The old binary installation images were retired in late 2023. They are still available for historical purposes, but are no longer updated.
-While the binaries on this page are fine, if you [[EMAN2:Install:SourceInstall|install from source]], then you can rapidly update when we make small patches to the code. Code is being developed continuously, and binaries are built only every few months.
+While the installation method on this page is fine, if you [[EMAN2:Install:SourceInstall|install from source]], then you can rapidly update when we make small patches to the code. Code is being developed continuously, and binaries are often built only every few months.
 ====== Install binary into Anaconda/MiniForge environment (all platforms) ======
@@ Line 54: / Line 54: @@
 </code>
-<<Anchor(GPU)>>
 ===== GPU Aceleration & Deep Learning =====
 Older EMAN2 programs make use of Tensorflow for Deep Learning/GPU support, but we have been gradually migrating to the new JAX library, so having both installed is strongly suggested.
@@ Line 60: / Line 59: @@
   * Tensorflow
     * Should be installed automatically as part of the EMAN2 environment setup above
-    * You can check to see what version of Tensorflow and whether it is GPU accelerated with: "conda list|grep tensorflow". On a machine with an NVIDIA GPU and properly configured drivers, you should see a tensorflow version like "2.17.0    cuda120py312h02ad488_203". This says that you are using the CUDA 12.0, Python 3.12 version of tensorflow 2.17.0. If you see "cpu" instead of "cuda" then you do not have GPU acceleration, and you will need to sort that out.
+    * You can check to see what version of Tensorflow and whether it is GPU accelerated with: //conda list|grep tensorflow//. On a machine with an NVIDIA GPU and properly configured drivers, you should see a tensorflow version like **2.17.0    cuda120py312h02ad488_203**. This says that you are using the CUDA 12.0, Python 3.12 version of tensorflow 2.17.0. If you see "cpu" instead of "cuda" then you do not have GPU acceleration, and you will need to sort that out.
     * You can test tensorflow with: //$CONDA_PREFIX/examples/test_tensorflow_basic.py//
@@ Line 66: / Line 65: @@
     * While it is possible to install JAX using conda/mamba, it can be difficult to find a version of GPU JAX and a version of GPU Tensorflow which will install properly together this way.
     * Instead, we strongly suggest just installing JAX using pip:
-      * conda activate eman2
+      <code>
-      * Linux (NVIDIA): pip install jax[cuda12]
+conda activate eman2
-      * Other (cpu): pip install jax
+# Linux (NVIDIA):
+pip install jax[cuda12] optax
+#Other (cpu):
+pip install jax optax
+      </code>
     * see [[https://pypi.org/project/jax/]] for up to date JAX instructions, this may change more frequently than this page is updated
     * You can test after installation with: //$CONDA_PREFIX/examples/test_jax_basic.py//