message: add training passes to nightly
diff: @@ -368,6 +368,67 @@ SUITES:
  keras-stripe-ocl-gfx804:
  prepend_args: [-n, 64]
  skip_platforms: [keras-plaid-ocl-gv100gl]
  + train:
  + platforms:
  + keras-tf-cuda-gp100gl:
  + pipelines: [nightly]
  + keras-plaid-ocl-gp100gl:
  + pipelines: [nightly, train]
  + keras-stripe-ocl-gp100gl:
  + pipelines: [nightly, train]
  + keras-plaid-ocl-gfx900:
  + pipelines: [nightly, train]
  + keras-stripe-ocl-gfx900:
  + pipelines: [nightly, train]
  + keras-plaid-ocl-neo:
  + pipelines: [nightly, train]
  + keras-stripe-ocl-neo:
  + pipelines: [nightly, train]
  + keras-plaid-ocl-gfx804:
  + pipelines: [nightly, train]
  + keras-stripe-ocl-gfx804:
  + pipelines: [nightly, train]
  + keras-plaid-mtl-uhd630:
  + pipelines: [nightly, train]
  + keras-stripe-mtl-uhd630:
  + pipelines: [nightly, train]
  +
  + params:
  + nightly:
  + batch_sizes: [1, 32]
  + train:
  + batch_sizes: [16, 32]
  + wheels:
  + # NOTE: this list must be in least to most dependent order.
  + - plaidml-{version}-py2.py3-none-{arch}.whl
  + - plaidml_keras-{version}-py2.py3-none-any.whl
  + - plaidbench-{version}-py2.py3-none-any.whl
  +
  + timeout: 5
  + conda_env: conda/ml_gpu.yml
  + cwd: plaidbench
  + runner: python
  + examples: 256
  + workloads:
  + inception_v3_train:
  + # Expecting a memory error -- the versions that are too big will skip;
  + # passing versions will pass; and non-memory errors will still error
  + expected: "CL_MEM_OBJECT_ALLOCATION_FAILURE"
  + precision: low
  + args: [plaidbench.py, inception_v3, --train, --print-stacktraces]
  + resnet50_train:
  + precision: low
  + args: [plaidbench.py, resnet50, --train, --print-stacktraces]
  + vgg19_train:
  + precision: low
  + args: [plaidbench.py, vgg19, --train, --print-stacktraces]
  + xception_train:
  + precision: low
  + args: [plaidbench.py, xception, --train, --print-stacktraces]
  + skip_platforms: keras-plaid-ocl-gp100gl
  + mobilenet_train:
  + precision: low
  + args: [plaidbench.py, mobilenet, --train, --print-stacktraces]
  comprehensive:
  platforms:
  