benchmarks/dlrm/ootb/dlrm_data_caffe2.py [598:624]:
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def generate_stack_distance(cumm_val, cumm_dist, max_i, i, enable_padding=False):
    u = ra.rand(1)
    if i < max_i:
        # only generate stack distances up to the number of new references seen so far
        j = bisect.bisect(cumm_val, i) - 1
        fi = cumm_dist[j]
        u *= fi  # shrink distribution support to exclude last values
    elif enable_padding:
        # WARNING: disable generation of new references (once all have been seen)
        fi = cumm_dist[0]
        u = (1.0 - fi) * u + fi  # remap distribution support to exclude first value

    for (j, f) in enumerate(cumm_dist):
        if u <= f:
            return cumm_val[j]


# WARNING: global define, must be consistent across all synthetic functions
cache_line_size = 1


def trace_generate_lru(
    line_accesses, list_sd, cumm_sd, out_trace_len, enable_padding=False
):
    max_sd = list_sd[-1]
    l = len(line_accesses)
    i = 0
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benchmarks/dlrm/ootb/dlrm_data_pytorch.py [1063:1089]:
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def generate_stack_distance(cumm_val, cumm_dist, max_i, i, enable_padding=False):
    u = ra.rand(1)
    if i < max_i:
        # only generate stack distances up to the number of new references seen so far
        j = bisect.bisect(cumm_val, i) - 1
        fi = cumm_dist[j]
        u *= fi  # shrink distribution support to exclude last values
    elif enable_padding:
        # WARNING: disable generation of new references (once all have been seen)
        fi = cumm_dist[0]
        u = (1.0 - fi) * u + fi  # remap distribution support to exclude first value

    for (j, f) in enumerate(cumm_dist):
        if u <= f:
            return cumm_val[j]


# WARNING: global define, must be consistent across all synthetic functions
cache_line_size = 1


def trace_generate_lru(
    line_accesses, list_sd, cumm_sd, out_trace_len, enable_padding=False
):
    max_sd = list_sd[-1]
    l = len(line_accesses)
    i = 0
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