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After v0.5.12: [Releases]
(April 11, 2020) v0.5.11 released
taichi-nightly now covers CUDA 10.X on Windows and Linux (#756) (by Yuanming Hu)game_of_life.py (#741) (by 彭于斌)examples/regression.py (#757) (by Quan Wang)ti.GUI.circles (#755) (by Yuanming Hu)continue on all backends (#716) (by Ye Kuang)ti.random() on Metal (#710) (by Ye Kuang)(Mar 29, 2020) v0.5.10 released
ti.static(ti.grouped(ti.ndrange(...))) syntax checker false positive (#680) (by Yuanming Hu)ti test now supports -t/--threads for specifying number of testing threads (#674) (by Yuanming Hu)(Mar 28, 2020) v0.5.9 released
bitmasked as the leaf block structure for 1x1x1 masks (#676) (by Yuanming Hu)bitmasked as the leaf block structure for 1x1x1 masks (#676) (by Yuanming Hu)bitmasked on Metal (#661) (by Ye Kuang)(Mar 24, 2020) v0.5.8 released. Visible/notable changes:
Expr.copy_from (by Yuanming Hu)ti.Vector.unit to generate unit vectors (by Yuanming Hu)a = ti.static(a_very_long_variable) for easy aliasing [doc] (#587) (by 彭于斌 and KLozes)ti.atomic_min, ti.atomic_max, ti.atomic_bit_or, ti.atomic_bit_and, ti.atomic_bit_xor (CPU and CUDA by KLozes, OpenGL by 彭于斌, Metal by Ye Kuang)ti format now cover all files from upstream/master to the working tree (#629) (by Ye Kuang)ti test now uses argparse for better customizability (#601) (by 彭于斌)examples/mgpcg.py (#573) (by KLozes)examples/sdf_renderer.py (by Yuanming Hu)examples/mgpcg_advanced.py (#573) (by Yuanming Hu)(Mar 4, 2020) v0.5.7 released
ti.classfunc. Please simply use ti.func, even if you are decorating a class member functionti test on release mode(Mar 3, 2020) v0.5.6 released
ti.GUI.line (by Mingkuan Xu [xumingkuan])arch=ti.arm64 is now supported. (Please build from source)(Mar 2, 2020) v0.5.5 released: Experimental CUDA 10.0/10.1 support on Windows. Feedbacks are welcome!
(Mar 1, 2020) v0.5.4 released
ti.imread/imwrite/imshow for convenient image IO (by Yubin Peng [archibate])ti.GUI.set_image now takes all numpy unsigned integer types (by Yubin Peng [archibate])1 < ti.append(...) < 3 < 4) (by Mingkuan Xu [xumingkuan])@ti.classkernel is deprecated. Always use ti.kernel, no matter you are decorating a class member function or not (by Ye Kuang [k-ye])TI_USE_UNIFIED_MEMORY=0 to disable unified memory usageti.GUI.line performance(Feb 25, 2020) v0.5.3 released
ti.warning renamed to ti.warn
ti.x86_64 renamed to ti.x64. ti.x86_64 is deprecated and will be removed in a future releaseu8, i8, u16, i16, u32 (by Yubin Peng [archibate])(Feb 20, 2020) v0.5.2 released
ti.pow now supported (by Yubin Peng [archibate])ti.pow (by Ye Kuang [k-ye])ti.normalized now optionally takes a argument eps to prevent division by zero in differentiable programmingTI_LOG_LEVEL to trace, debug, info, warn, error to filter out/increase verbosity. Default=info
ti.GUI.triangle example
ti.cross for 3D cross productsTI_TEST_THREADS to override testing threadsti.init(print_processed=True) renamed to ti.init(print_preprocessed=True)
(Feb 16, 2020) v0.5.1 released
ti (ti.exe) command supported on Windows after setting %PATH% correctly (by Mingkuan Xu [xumingkuan])x ** y now supported in Taichi kernels (by Yubin Peng [archibate]).dense(...).pointer() now abbreviated as .pointer(...). pointer now stands for a dense pointer array. This leads to cleaner code and better performance. (by Kenneth Lozes [KLozes])for i in X now iterates all child instances of X instead of X itself. Skip this if you only use X=leaf node such as ti.f32/i32/Vector/Matrix.(Feb 14, 2020) v0.5.0 released with a new Apple Metal GPU backend for Mac OS X users! (by Ye Kuang [k-ye])
ti.init(..., arch=ti.metal) and run Taichi on your Mac GPUs!dense SNodes and 32-bit data types. It doesn't support ti.random() or print().[] operator in Python is slow in the current implementation. If you need to do a large number of reads, consider dumping all the data to a numpy array via to_numpy() as a workaround. For writes, consider first generating the data into a numpy array, then copying that to the Taichi variables as a whole.(Feb 12, 2020) v0.4.6 released.
TAICHI_REPO_DIR is not a valid path (by Yubin Peng [archibate])ti.require() and ti.archs_excluding() (by Ye Kuang [k-ye])ti.init(**kwargs) now takes a parameter debug=True/False, which turns on debug mode if trueTI_DEBUG=1 to turn on debug mode non-intrusivelyti.profiler_clear
GUI.line(begin, end, color, radius) and ti.rgb_to_hex
ti.trace (Matrix trace) to ti.tr. ti.trace is now for logging with ti.TRACE levelti test_cpp (thanks to Ye Kuang [k-ye])ti.INFO instead of trace to make the world quiter(Feb 6, 2020) v0.4.5 released.
ti.init(arch=..., print_ir=..., default_fp=..., default_ip=...) now supported. ti.cfg.xxx is deprecatedti.init. No need to wrap data layout definition with @ti.layout anymore (unless you intend to do so)ti.is_active, ti.deactivate, SNode.deactivate_all supported in the new LLVM x64/CUDA backend. Example 
ti.global_var (which duplicates ti.var) is removedti.Matrix.rotation2d(angle) added(Feb 5, 2020) v0.4.4 released.
f64 precision support of sin and cos on CUDA backends (by Kenneth Lozes [KLozes])Profiler working on CPU devices. To enable, ti.cfg.enable_profiler = True. Call ti.profiler_print() to print kernel running times(Feb 3, 2020) v0.4.3 released.
GUI.circles 2.4x faster(Feb 2, 2020) v0.4.2 released.
mpm88.py is 30% faster on CUDA due to reduced kernel launches(Jan 31, 2020) v0.4.1 released.
Dockerfile (by Shenghang Tsai [jackalcooper])pbf2d.py visualization performance boosted (by Ye Kuang [k-ye])GlobalTemporaryStmt codegen(Jan 30, 2020) v0.4.0 released.
ti.deactivate now supported on sparse data structuresGUI.circles (batched circle drawing) performance improved by 30x(Jan 20, 2020) v0.3.25 released.
(Jan 19, 2020) v0.3.24 released.
% and // now follow Python semantics. Use ti.raw_mod for C-style % semantics (by Chujie Zeng [Psycho7])for i in range(bound[0]) is supported(Jan 18, 2020) v0.3.23 released.
(Jan 17, 2020) v0.3.22 released.
ti.atomic_add() now returns the old value (by Ye Kuang [k-ye])ti.__version__ now returns the version triple, e.g. (0, 3, 22)
ti.cfg.print_ir = True
ti.cfg.print_accessor_ir
(Jan 11, 2020) v0.3.21 released.
(Jan 2, 2020) v0.3.20 released.
ti.static(ti.grouped(ti.ndrange(...)))
(Jan 2, 2020) v0.3.19 released.
ti.atan2(y, x)
(Jan 1, 2020) v0.3.18 released.
ti.GUI classti.Matrix.fill
(Dec 31, 2019) v0.3.17 released.
ti.Matrix.T() for transposing a matrixti.static(ti.ndrange)
ti.Matrix.identity()
ti.Matrix.one() (create a matrix with 1 as all the entries)ir_printer on SNodesdynamic SNodes.
Struct-for's on dynamic nodes supportedti.length and ti.append to query and manipulate dynamic nodes(Dec 29, 2019) v0.3.16 released.
(Dec 28, 2019) v0.3.15 released.
ti.ndrange: @ti.kernel
def fill_3d():
# Parallelized for all 3 <= i < 8, 1 <= j < 6, 0 <= k < 9
for i, j, k in ti.ndrange((3, 8), (1, 6), 9):
x[i, j, k] = i + j + k
ti and tid (debug mode) CLI commandsti.append now returns the list length before appendingti.get_runtime().set_verbose_kernel_launch(True) to log kernel launches/ and // following the Python conventiondynamic node support (ti.append, ti.length) in the new LLVM backendassert <condition> statement supported in Taichi kernels.1 < x <3) supported in Taichi kernels.ti.classfunc decorator for functions within a data_oriented class[Expr/Vector/Matrix].to_torch now has a extra argument device, which specifies the device placement for returned torch tensor, and should have type torch.device. Default=None.to_torch/from_torch.matrix size to 1)ti.data_oriented decorator introduced. Please decorate all your Taichi data-oriented objects using this decorator. To invoke the gradient versions of classmethod, for example, A.forward, simply use A.forward.grad() instead of A.forward(__gradient=True) (obsolete).R, S = ti.polar_decompose(A, ti.f32)) and svd (U, sigma, V = ti.svd(A, ti.f32)) support. Note that sigma is a 3x3 diagonal matrix.expr_init with ti.core.DataType as inputs, so that ti.core.DataType can be used as ti.func parameterDiffTaichi examples moved to a standalone repo
Vector.norm now comes with a parameter eps (=0 by default), and returns sqrt(\sum_i(x_i ^ 2) + eps). A non-zero eps safe guards the operator's gradient on zero vectors during differentiable programming.glibc 2.27
break statements supported in while loopsti.GUI.set_image(np.ndarray/Taichi tensor)x[i] += j is equivalent to ti.atomic_add(x[i], j)
ti.func arguments are forced to pass by valuemin/max can now take more than two arguments, e.g. max(a, b, c, d)
transposed, trace, polar_decompose, determinant promoted to ti scope. I.e., users can now use ti.transposed(M) instead of ti.Matrix.transposed(M)
ti.get_runtime().set_verbose(False) to eliminate verbose outputsti.random(ti.i32/i64/f32/f64)Taichi, numpy and PyTorch
taichi_scalar_tensor.to_numpy()/from_numpy(numpy_array)taichi_scalar_tensor.to_torch()/from_torch(torch_array)ti.ext_arr() now takes PyTorch tensorsmin/max supprtMatrix.to_numpy, Matrix.zero, Matrix.identity, Matrix.fill
ti.static
numpy arrays passed as a ti.ext_arr() [examples]
i32/f32/i64/f64 data type support for numpyTensor.to_numpy() and Tensor.from_numpy(numpy.ndarray) supported [examples]
ti.ext_arr(). Please use numpy arrays as intermediate buffers for nowTensor.dim() to retrieve the dimensionality of a global tensorTensor.shape() to retrieve the shape of a global tensorstruct-for (e.g. for i, j in x) now supports iterating over tensors with non power-of-two dimensionsTensor.fill(x) to set all entries to x
Matrix.fill(x) to set all entries to x, where x can be a scalar or ti.Matrix of the same sizestruct-for with grouped indices for better metaprogramming, especially in writing dimensionality-independent code, in e.g. physical simulation: [examples]
for I in ti.grouped(x): # I is a vector of size x.dim() and data type i32
x[I] = 0
# If tensor x is 2D
for I in ti.grouped(x): # I is a vector of size x.dim() and data type i32
y[I + ti.Vector([0, 1])] = I[0] + I[1]
# is equivalent to
for i, j in x:
y[i, j + 1] = i + j
(Nov 27, 2019) v0.1.5 released.
ti.static outside Taichi kernels(Nov 22, 2019) v0.1.3 released.
print instead of ti.print
int() instead of ti.cast(x, ti.i32) (or ti.cast(x, ti.i64) if your default integer precision is 64 bit)float() instead of ti.cast(x, ti.f32) (or ti.cast(x, ti.f64) if your default float-point precision is 64 bit)abs instead of ti.abs
ti.static_print for compile-time printing(Nov 16, 2019) v0.1.0 released. Fixed PyTorch interface.
(Nov 12, 2019) v0.0.87 released.
(Nov 4, 2019) v0.0.85 released.
ti.stop_grad for stopping gradients during backpropagation. [Example];The legacy Taichi library is an open-source computer graphics library written in C++14 and wrapped friendly with Python. It is no longer maintained since we have switched to the Taichi programming language and compiler.
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