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Results 1 - 2 of 2 for sqr_sum (0.12 sec)
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tensorflow/compiler/mlir/lite/ir/tfl_ops.td
each component is divided by the weighted, squared sum of inputs within `depth_radius`. In detail, sqr_sum[a, b, c, d] = sum(input[a, b, c, d - depth_radius : d + depth_radius + 1] ** 2) output = input / (bias + alpha * sqr_sum) ** beta For details, see [Krizhevsky et al., ImageNet classification with deep
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
each component is divided by the weighted, squared sum of inputs within `depth_radius`. In detail, sqr_sum[a, b, c, d] = sum(input[a, b, c, d - depth_radius : d + depth_radius + 1] ** 2) output = input / (bias + alpha * sqr_sum) ** beta For details, see [Krizhevsky et al., ImageNet classification with deep
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)