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Results 1 - 3 of 3 for dimension (0.04 sec)

  1. cmd/format-erasure.go

    		This    string `json:"this"`    // This field carries assigned disk uuid.
    		// Sets field carries the input disk order generated the first
    		// time when fresh disks were supplied, it is a two dimensional
    		// array second dimension represents list of disks used per set.
    		Sets [][]string `json:"sets"`
    		// Distribution algorithm represents the hashing algorithm
    		// to pick the right set index for an object.
    Registered: Sun Sep 07 19:28:11 UTC 2025
    - Last Modified: Fri Aug 29 02:39:48 UTC 2025
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  2. RELEASE.md

            control flow.
        *   Add `RaggedTensor.numpy()`.
        *   Update `RaggedTensor.__getitem__` to preserve uniform dimensions & allow
            indexing into uniform dimensions.
        *   Update `tf.expand_dims` to always insert the new dimension as a
            non-ragged dimension.
        *   Update `tf.embedding_lookup` to use `partition_strategy` and `max_norm`
            when `ids` is ragged.
    Registered: Tue Sep 09 12:39:10 UTC 2025
    - Last Modified: Mon Aug 18 20:54:38 UTC 2025
    - 740K bytes
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  3. tensorflow/c/c_api_experimental.cc

      DCHECK(index >= 0 && index < shape_list->num_items);
      TF_ShapeAndType& shape = shape_list->items[index];
      DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
      DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
      shape.num_dims = num_dims;
      shape.dims = new int64_t[num_dims];
      memcpy(shape.dims, dims, sizeof(int64_t) * num_dims);
    }
    
    Registered: Tue Sep 09 12:39:10 UTC 2025
    - Last Modified: Mon Aug 18 03:53:25 UTC 2025
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