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"""Performance benchmark tests for MXNet NDArray Unary Operations.
1. Operators are automatically fetched from MXNet operator registry.
2. Default Inputs are generated. See rules/default_params.py. You can override the default values.

Below 54 unary Operators are covered:

['BlockGrad', 'Flatten', 'abs', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctanh',
'argmax_channel', 'cbrt', 'ceil', 'cos', 'cosh', 'degrees', 'erf', 'erfinv', 'exp', 'expm1', 'fix', 'flatten',
'floor', 'gamma', 'gammaln', 'identity', 'log', 'log10', 'log1p', 'log2', 'logical_not', 'make_loss', 'negative',
'ones_like', 'radians', 'rcbrt', 'reciprocal', 'relu', 'rint', 'round', 'rsqrt', 'shuffle', 'sigmoid', 'sign',
'sin', 'sinh', 'size_array', 'softsign', 'sqrt', 'square', 'stop_gradient', 'tan', 'tanh', 'trunc', 'zeros_like']

"""

import mxnet as mx

from benchmark.opperf.utils.op_registry_utils import get_all_unary_operators
from benchmark.opperf.utils.benchmark_utils import run_op_benchmarks


def run_mx_unary_operators_benchmarks(ctx=mx.cpu(), dtype='float32', warmup=25, runs=100):
    """Runs benchmarks with the given context and precision (dtype)for all the unary
    operators in MXNet.

    Parameters
    ----------
    ctx: mx.ctx
        Context to run benchmarks
    dtype: str, default 'float32'
        Precision to use for benchmarks
    warmup: int, default 25
        Number of times to run for warmup
    runs: int, default 100
        Number of runs to capture benchmark results

    Returns
    -------
    Dictionary of results. Key -> Name of the operator, Value -> Benchmark results.

    """
    # Fetch all Unary Operators
    mx_unary_broadcast_ops = get_all_unary_operators()
    # Run benchmarks
    mx_unary_op_results = run_op_benchmarks(mx_unary_broadcast_ops, dtype, ctx, warmup, runs)
    return mx_unary_op_results
