1 files changed, 0 insertions, 119 deletions
diff --git a/benchmarks/suites/__init__.py b/benchmarks/suites/__init__.py
deleted file mode 100644
index 360736cc3..000000000
--- a/benchmarks/suites/__init__.py
+++ /dev/null
@@ -1,119 +0,0 @@
-# python3
-# Copyright 2019 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""Core benchmark annotations."""
-
-import functools
-import inspect
-import types
-from typing import List
-from typing import Tuple
-
-BENCHMARK_METRICS = '__benchmark_metrics__'
-BENCHMARK_MACHINES = '__benchmark_machines__'
-
-
-def is_benchmark(func: types.FunctionType) -> bool:
-  """Returns true if the given function is a benchmark."""
-  return isinstance(func, types.FunctionType) and \
-      hasattr(func, BENCHMARK_METRICS) and \
-      hasattr(func, BENCHMARK_MACHINES)
-
-
-def benchmark_metrics(func: types.FunctionType) -> List[Tuple[str, str]]:
-  """Returns the list of available metrics."""
-  return [(metric.__name__, metric.__doc__)
-          for metric in getattr(func, BENCHMARK_METRICS)]
-
-
-def benchmark_machines(func: types.FunctionType) -> int:
-  """Returns the number of machines required."""
-  return getattr(func, BENCHMARK_MACHINES)
-
-
-# pylint: disable=unused-argument
-def default(value, **kwargs):
-  """Returns the passed value."""
-  return value
-
-
-def benchmark(metrics: List[types.FunctionType] = None,
-              machines: int = 1) -> types.FunctionType:
-  """Define a benchmark function with metrics.
-
-  Args:
-    metrics: A list of metric functions.
-    machines: The number of machines required.
-
-  Returns:
-    A function that accepts the given number of machines, and iteratively
-    returns a set of (metric_name, metric_value) pairs when called repeatedly.
-  """
-  if not metrics:
-    # The default passes through.
-    metrics = [default]
-
-  def decorator(func: types.FunctionType) -> types.FunctionType:
-    """Decorator function."""
-    # Every benchmark should accept at least two parameters:
-    #   runtime: The runtime to use for the benchmark (str, required).
-    #   metrics: The metrics to use, if not the default (str, optional).
-    @functools.wraps(func)
-    def wrapper(*args, runtime: str, metric: list = None, **kwargs):
-      """Wrapper function."""
-      # First -- ensure that we marshall all types appropriately. In
-      # general, we will call this with only strings. These strings will
-      # need to be converted to their underlying types/classes.
-      sig = inspect.signature(func)
-      for param in sig.parameters.values():
-        if param.annotation != inspect.Parameter.empty and \
-           param.name in kwargs and not isinstance(kwargs[param.name], param.annotation):
-          try:
-            # Marshall to the appropriate type.
-            kwargs[param.name] = param.annotation(kwargs[param.name])
-          except Exception as exc:
-            raise ValueError(
-                'illegal type for %s(%s=%s): %s' %
-                (func.__name__, param.name, kwargs[param.name], exc))
-        elif param.default != inspect.Parameter.empty and \
-             param.name not in kwargs:
-          # Ensure that we have the value set, because it will
-          # be passed to the metric function for evaluation.
-          kwargs[param.name] = param.default
-
-      # Next, figure out how to apply a metric. We do this prior to
-      # running the underlying function to prevent having to wait a few
-      # minutes for a result just to see some error.
-      if not metric:
-        # Return all metrics in the iterator.
-        result = func(*args, runtime=runtime, **kwargs)
-        for metric_func in metrics:
-          yield (metric_func.__name__, metric_func(result, **kwargs))
-      else:
-        result = None
-        for single_metric in metric:
-          for metric_func in metrics:
-            # Is this a function that matches the name?
-            # Apply this function to the result.
-            if metric_func.__name__ == single_metric:
-              if not result:
-                # Lazy evaluation: only if metric matches.
-                result = func(*args, runtime=runtime, **kwargs)
-              yield single_metric, metric_func(result, **kwargs)
-
-    # Set metadata on the benchmark (used above).
-    setattr(wrapper, BENCHMARK_METRICS, metrics)
-    setattr(wrapper, BENCHMARK_MACHINES, machines)
-    return wrapper
-
-  return decorator