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In cl/234179031, we improved this test to use `os.path.join` rather than
a hard-coded `+ "/tb"` in a few places, but apparently missed some.

Tested:
After 1036s/tb/something_else/, tests still pass on my local gLinux
desktop. Before this change, tests would fail after that substitution,
albeit not for the same reason as the traceback in b/125762969: we get a
normal `assertItemsEqual` failure rather than an ENOENT. Running Kokoro
Windows presubmits per go/tf-testing passes.

RELNOTES: n/a
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- Disable `run_eagerly` and distribution strategy if there are symbolic tensors added to the model using `add_metric` or `add_loss`.
- Added error message for when subclassed model/Sequential model without input_shape is used with DS.
- Add error message when `run_eagerly` is enabled with DS.

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Previously, the tuple would be unpacked in string formatting, and if it had more than one element we would get an argument unpacking error, instead of the intended TypeError.

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Internal users of these properties should now use dataset_ops.get_legacy_output_{shapes,types,classes}() instead. In a future CL we will remove the properties from the DatasetV2.

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Provides better memory locality which speeds up most ops, and makes destruction trivial.

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An unfortunate combination of the name_scope method wrapping not forwarding argspecs and input_signatures inspecting functions for keyword arguments.

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Notice that most of the constants created by the constant folding pass are already in compressed format. This just extends this practice to all constants in the graph that have at least 64 elements and where the achievable compression ratio is grater or equal to 2.

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Renames to prepare for the TF2.0 API. HashTable -> StaticHashTable and MutableDenseHashTable -> DenseHashTable. Also insert -> insert_or_assign and remove -> erase for DenseHashTable.

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This function previously stated that it could accept a rank-0 Tensor as its `num_or_size_splits` argument. This is in fact not correct: TF graphs must have a static number of output tensors for any operation, so the number of splits has to be known statically or we cannot validate the correctness of the graph.

This method will now raise a ValueError if called with a rank-0 Tensor. I also make the documentation more explicit. Strangely, the test was testing for the incorrect behaviour, so I also fixed that.

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Previously, when in a GPU device context, the logic attempted to create the default empty metadata tensor on the GPU, which fails since it's a string tensor.

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Add implementations for CUDA library functions which dynamically load the CUDA library DSO and forward the call to the actual function. Most of the code is auto-generated.

Libraries implemented: CUDA driver API, cuRAND, cuFFT, cuBLAS, and cuDNN. The CUDA runtime is not implemented because it's not clear whether it should just be linked statically.

Older versions of CUDA (starting with 8.0) and cuDNN (starting with 7.0) are handled with two approaches:
- if the API didn't change and only new functions were added, declare types that were introduced afterwards. It is acceptable to implement APIs that were only introduced later: if they are called despite not being declared (in older headers), they will not be able to dlsym the corresponding function and return an error.
- if the API changed, different contextual headers are included.

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Replace angle bracket CUDA kernel launches ('<<<>>>') with API function calls ('cudaLaunchKernel'), through a helper function which also checks the return code in debug builds.

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