Minor foundation update

.github/workflows/virtual-environments.yml

@@ -55,4 +55,4 @@ jobs:
             # Run Scikeras Python Package Test
             dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.ScikerasTest" --blame-hang-timeout 120seconds --blame-crash
             # Run Transformers
-            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Transformers" --blame-hang-timeout 120seconds --blame-crash
+            dotnet test ./Tests/bin/Release/QuantConnect.Tests.dll --filter "FullyQualifiedName=QuantConnect.Tests.Python.PythonPackagesTests.Transformers|XTransformers" --blame-hang-timeout 120seconds --blame-crash

DockerfileLeanFoundation

@@ -200,9 +200,7 @@ RUN pip install --no-cache-dir      \
     jupyter-bokeh==3.0.7            \
     imbalanced-learn==0.11.0        \
     scikeras==0.12.0                \
-    openai==0.28.1                  \
-    openai[embeddings]==0.28.1      \
-    openai[wandb]==0.28.1           \
+    openai==1.3.5                   \
     lazypredict==0.2.12             \
     fracdiff==0.9.0                 \
     darts==0.24.0                   \
@@ -224,14 +222,16 @@ RUN pip install --no-cache-dir      \
     tick==0.7.0.1                   \
     transformers==4.34.0            \
     Rbeast==0.1.16                  \
-    langchain==0.0.316              \
+    langchain==0.0.341              \
     tensorflow-ranking==0.5.3       \
     pomegranate==1.0.3              \
     tigramite==5.2.3.1              \
     MAPIE==0.7.0                    \
     mlforecast==0.9.3               \
     functime==0.8.4                 \
-    tensorrt==8.6.1.post1
+    tensorrt==8.6.1.post1           \
+    x-transformers==1.26.0          \
+    Werkzeug==2.3.8
 
 RUN conda install -c conda-forge -y cudatoolkit=11.8.0 && conda install -c nvidia -y cuda-compiler=12.2.2 && conda clean -y --all
 ENV XLA_FLAGS=--xla_gpu_cuda_data_dir=/opt/miniconda3/
@@ -242,7 +242,7 @@ ENV CUDA_MODULE_LOADING=LAZY
 RUN dwave install --all -y
 
 # Install 'ipopt' solver for 'Pyomo'
-RUN conda install -c conda-forge ipopt==3.14.12 \
+RUN conda install -c conda-forge ipopt==3.14.13 \
     && conda clean -y --all
 
 # We install need to install separately else fails to find numpy

DockerfileLeanFoundationARM

@@ -183,9 +183,7 @@ RUN pip install --no-cache-dir      \
     jupyter-bokeh==3.0.7            \
     imbalanced-learn==0.11.0        \
     scikeras==0.12.0                \
-    openai==0.28.1                  \
-    openai[embeddings]==0.28.1      \
-    openai[wandb]==0.28.1           \
+    openai==1.3.5                   \
     lazypredict==0.2.12             \
     fracdiff==0.9.0                 \
     darts==0.24.0                   \
@@ -204,18 +202,20 @@ RUN pip install --no-cache-dir      \
     Shimmy==1.3.0                   \
     FixedEffectModel==0.0.5         \
     transformers==4.34.0            \
-    langchain==0.0.316              \
+    langchain==0.0.341              \
     tensorflow-ranking==0.5.3       \
     pomegranate==1.0.3              \
     tigramite==5.2.3.1              \
     MAPIE==0.7.0                    \
-    mlforecast==0.9.3
+    mlforecast==0.9.3               \
+    x-transformers==1.26.0          \
+    Werkzeug==2.3.8
 
 # Install dwave tool
 RUN dwave install --all -y
 
 # Install 'ipopt' solver for 'Pyomo'
-RUN conda install -c conda-forge ipopt==3.14.12 \
+RUN conda install -c conda-forge ipopt==3.14.13 \
     && conda clean -y --all
 
 # We install need to install separately else fails to find numpy

Tests/Python/PythonPackagesTests.cs

@@ -17,13 +17,42 @@
 using System;
 using Python.Runtime;
 using NUnit.Framework;
-using QuantConnect.Python;
 
 namespace QuantConnect.Tests.Python
 {
     [TestFixture, Category("TravisExclude")]
     public class PythonPackagesTests
     {
+        [Test, Explicit("Needs to be run by itself to avoid hanging")]
+        public void XTransformers()
+        {
+            AssertCode(
+                @"
+import torch
+from x_transformers import XTransformer
+
+def RunTest():
+    model = XTransformer(
+        dim = 512,
+        enc_num_tokens = 256,
+        enc_depth = 6,
+        enc_heads = 8,
+        enc_max_seq_len = 1024,
+        dec_num_tokens = 256,
+        dec_depth = 6,
+        dec_heads = 8,
+        dec_max_seq_len = 1024,
+        tie_token_emb = True      # tie embeddings of encoder and decoder
+    )
+
+    src = torch.randint(0, 256, (1, 1024))
+    src_mask = torch.ones_like(src).bool()
+    tgt = torch.randint(0, 256, (1, 1024))
+
+    loss = model(src, tgt, mask = src_mask) # (1, 1024, 512)
+    loss.backward()");
+        }
+
         [Test]
         public void Functime()
         {