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[DOCS] Fix typos (#2097)
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@@ -55,7 +55,7 @@ def randint(seed, offset, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
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using `randint4x` is likely to be faster than calling `randint` 4 times.
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:param seed: The seed for generating random numbers.
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:param offsets: The offsets to generate random numbers for.
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:param offset: The offsets to generate random numbers for.
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"""
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ret, _, _, _ = randint4x(seed, offset, n_rounds)
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return ret
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@@ -120,7 +120,7 @@ def rand(seed, offset, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
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def rand4x(seed, offsets, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
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"""
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Given a :code:`seed` scalar and an :code:`offsets` block,
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returns a 4 blocks of random :code:`float32` in :math:`U(0, 1)`.
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returns 4 blocks of random :code:`float32` in :math:`U(0, 1)`.
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:param seed: The seed for generating random numbers.
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:param offsets: The offsets to generate random numbers for.
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@@ -167,7 +167,7 @@ def randn(seed, offset, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
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def randn4x(seed, offset, n_rounds: tl.constexpr = N_ROUNDS_DEFAULT):
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"""
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Given a :code:`seed` scalar and an :code:`offset` block,
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returns a 4 blocks of random :code:`float32` in :math:`\\mathcal{N}(0, 1)`.
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returns 4 blocks of random :code:`float32` in :math:`\\mathcal{N}(0, 1)`.
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:param seed: The seed for generating random numbers.
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:param offsets: The offsets to generate random numbers for.
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@@ -192,7 +192,7 @@ def truediv(input: tl.tensor,
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elif input_scalar_ty.is_int() and other_scalar_ty.is_int():
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input = cast(input, tl.float32, builder)
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other = cast(other, tl.float32, builder)
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# float / float (cast to highest exponent type)
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# float / float (cast to the highest exponent type)
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elif input_scalar_ty.is_floating() and other_scalar_ty.is_floating():
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if input_scalar_ty.fp_mantissa_width > other_scalar_ty.fp_mantissa_width:
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other = cast(other, input_scalar_ty, builder)
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@@ -1364,7 +1364,7 @@ def associative_scan(
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def _check_dtype(dtypes: List[str]) -> T:
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"""
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We following libdevice's convention to check accepted data types for math functions.
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We're following libdevice's convention to check accepted data types for math functions.
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It is not a good practice to support all data types as accelerators/GPUs don't support
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many float16 and bfloat16 math operations.
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We should let the users know that they are using and invoke explicit cast to convert
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